MOBILE ROBOT FOR SEARCH AND RESCUE
A Thesis Presented to
The Faculty of the
Fritz J. and Dolores H. Russ College of Engineering and Technology
Ohio University
In Partial Fulfillment
Of the Requirements for the Degree
Master of Science
BY
Jansen J Litter
June 2004 Table of Contents Page
List of Figures ...... v
List of Tables ...... ix
List of Symbols ...... x
1. Introduction ...... 1
1.1 Literature Review ...... 1
1.2 Thesis Objectives ...... 9
2 . Project Background ...... 10
2.1 Ohio University's Interest ...... 10
2.2 Our Approach to the Competition ...... 11
2.3 NIST Field Overview ...... 12
2.4 Planned Vehicle Use Now and In The Future ...... 16
3 . Preliminary Design Approach ...... 18
3.1 Overview of Existing Robots ...... 18
3.2 Power-Wheels Concept ...... 23
3.3 Arm-Linked Robot Concept ...... 27
4 . Final Design Approach ...... 35
4.1 Mechanical Design ...... 35
4.1.1 Frame Design ...... 35
4.1.2 Motor Sizing ...... 38
4.1.3 Tire Determination ...... 42 iv
4.1.4 Solid Edge. Algor and Visual Nastran ...... 44
4.1.5 Additional Design Considerations ...... 60
4.2 Electrical Design ...... 65
4.2.1 Power system ...... 66
4.2.2 Motor Controllers and Sensors ...... 68
5 . Mobile Robot Control ...... 73
5.1 Open-Loop Control ...... 73
5.2 Closed Loop Control ...... 77
5.3 Controlled Motion ...... 79
6 . Results ...... 82
6.1 Velocity, Acceleration, and Braking ...... 83
6.2 Traction on Linoleum. Concrete. and Grass ...... 88
6.3 Turning ...... 89
6.4 Commanded vs . Actual Motion ...... 91
6.4 Motion with Encoders vs . Motion without Encoders ...... 92
6.5 Frame Stiffness ...... 93
6.6 Operational Procedures ...... 93
7 . Conclusions ...... 95
References ...... 98 List of Figures Page
Figure 1.1 Vasilius ...... 2
Figure 1.2 Centurion ...... 3
Figure 1.3 Fast ...... 3
Figure 1.4 Eliminator ...... 4
Figure 1.5 Eliminator (before modification) ...... 4
Figure 1.6 The Kodiak ...... 5
Figure 1.7 The Kodiak at a Convention ...... 5
Figure 1.8 Bear Cub ...... 6
Figure 1.9 Polar Bear ...... 6
Figure 1.10 Georgia Tech Mobile Robot Lab Image of Hallway by SICK LMS ...... 7
Figure 1.1 1 Georgia Tech Mobile Robot Lab Image of People by SICK LMS ...... 7
Figure 1.12 Georgia Tech Mobile Robot ...... 8
Figure 1.13 NIST Robot ...... 8
Figure 1.14 NIST Hallway Model ...... 9
Figure 2.1 NIST Arena ...... 14
Figure 2.2 NIST Arena Diagram ...... 15
Figure 2.3 NIST Victims ...... 15
Figure 2.4 Victim Description ...... 16
Figure 3.1 ART 1 ...... 19
Figure 3.2 ATRV-2 ...... 20
Figure 3.3 ATRV Jr ...... 20 vi
Figure 3.4 Packbot ...... 21
Figure 3.5 GAIA-2 ...... 21
Figure 3.6 W.A.T.V ...... 22
Figure 3.7 Kadtronix Frame ...... 22
Figure 3.8 Power-Wheels Toy Car ...... 24
Figure 3.9 Chassis Schematic of Power-Wheels ...... 24
Figure 3.10 Robot Body Concept ...... 28
Figure 3.1 1 Arm ...... 29
Figure 3.12 Body with Arm Attached ...... 30
Figure 3.13 Bodies Connected ...... 31
Figure 3.14 Beginning to Climb ...... 32
Figure 3.15 Climbing ...... 32
Figure 3.16 Continuing to Climb ...... 33
Figure 3.17 SICK LMS 200 ...... 34
Figure 4.1 Aluminum Frame ...... 36
Figure 4.2 Aluminum 606 1-T6 Structural Members ...... 37
Figure 4.3 NPC-T64 Motor ...... 38
Figure 4.4 NPC-T64 Dynamometer Results ...... 39
Figure 4.5 Dynamic Model ...... 40
Figure 4.6 Tire Tread Pattern ...... 43
Figure 4.7 Frame with Motors ...... 45
Figure 4.8 Aluminum Frame, Motors, Tires, Batteries and Controllers ...... 45 vii
Figure 4.9 Carbon Steel Frame ...... 47
Figure 4.10 Stress of Aluminum Frame at 6psi Uniform Pressure ...... 48
Figure 4.1 1 Displacement of Aluminum Frame in Z direction ...... 49
Figure 4.12 Stress of Carbon Steel Frame at lopsi Uniform Pressure ...... 50
Figure 4.13 Displacement of Carbon Steel Frame in Z Direction ...... 51
Figure 4.14 Torque Applied at Front, Rear Fixed ...... 53
Figure 4.15 Torque Applied to Right Side, Rear Fixed ...... 54
Figure 4.16 Torque Applied at Each Corner. Rear Fixed ...... 55
Figure 4.17 Fixed at One Corner. Max Torque on Other Three ...... 56
Figure 4.18 Point Loading. Fixed in Rear ...... 57
Figure 4.19 800in-lbs Torque at Front. Rear Fixed ...... 58
Figure 4.20 All Four Motors Outputting Max Torque ...... 59
Figure 4.2 1 Point Loading of Frame ...... 60
Figure 4.22 Frame with Motor Mounts ...... 61
Figure 4.23 Frame with Motors in Mounts ...... 61
Figure 4.24 Bottom View of Frame with CAD Model ...... 62
Figure 4.25 Complete Frame with CAD Model ...... 62
Figure 4.26 Frame with Top Open ...... 63
Figure 4.27 Completed Robot with CAD Model IS0 View ...... 63
Figure 4.28 Completed Robot with CAD Model Rear View ...... 64
Figure 4.29 Pin Jointed Aluminum Frame with CAD Model ...... 64
Figure 4.30 Frame Rotated With CAD Model ...... 65 ... Vlll
Figure 4.3 1 Conceptual CAD Model of Frame Rotation with Motors and Tires ...... 65
Figure 4.32 Wire. Connectors. Terminals and Fuses ...... 67
Figure 4.33 Roboteq AX2550 ...... 69
Figure 4.34 Renco Optical Encoders ...... 70
Figure 4.35 Futaba 9CAP Transmitter. Receiver. with Battery and AX2550 Harness ... 71
Figure 5.1 Remote Control Open-Loop with No Feedback ...... 74
Figure 5.2 Open-Loop Remote Control with Encoder Feedback ...... 75
Figure 5.3 Closed-Loop Control Through Computer with Feedback ...... 76
Figure 5.4 Skid-Steering ...... 79
Figure 5.5 Differential-Steering ...... 80
Figure 6.1 Grass Field with White Yard Marker ...... 84
Figure 6.2 Concrete Pad with Joints 6ft Apart ...... 84
Figure 6.3 Pushing the Robot onto its Wheels ...... 88
Figure 6.4 Dragging Jason Norman ...... 89
Figure 6.5 Robot Drifting to Right ...... 92 List of Tables Page
Table 6.1 Robot Velocity and Acceleration Data for Grass Field ...... 86
Table 6.2 Robot Velocity and Acceleration Data for Brushed Concrete ...... 87 List of Symbols
Weight of the robot in the X direction (Ibs)
Static friction force (lbs)
Normal force (Ibs)
Motor torque (in-lbs)
Stall torque (in-lbs)
Radius of the tire (in)
Force of the motor (lbs)
System mass (Ibm)
Acceleration of the robot (ft/sec2)
Stall angle to be overcome by robot (degrees)
Initial distance traveled by robot (ft)
Final distance traveled by robot (ft)
Constant velocity of robot (ftlsec)
Initial velocity of robot (ftlsec)
Acceleration of robot (ft/sec2)
Time (sec) 1. Introduction
RoboCupRescue is a part of RoboCup, which is an international robotics competition held to inspire people to field autonomous robots capable of playing soccer.
RoboCupRescue is a competition that focuses on building robots to search for human survivors and aid rescue personnel during a large scale disaster. Inspiration for this branch of RoboCup stems from the 1995 earthquake that hit Kobe, Japan. This earthquake killed 6,432 people an injured and estimated 43,800 according to hospital records (A1 Magazine spring 2001). RoboCup inspires cooperation among multi-agent robots, has an ever changing dynamic environment, and utilizes autonomy. Due to the events of September 1 lth2001 and natural disasters, search and rescue mobile robotics has become a necessity in the U.S. Many of the robots that went to the World Trade
Center failed during the course of their search and rescue operations. This creates a need for more people to become involved and help develop the field of search and rescue mobile robotics towards improved operations.
1.1 Literature Review
Bluefield State College offers a couple of ground based mobile robotic vehicles that would be suited for search and rescue applications as well as outdoor autonomous use (they were designed for this purpose). The first is the Vasilius (Figure 1.1) it is important to our project for two reasons.
First, it is using the SICK LMS laser ranging unit as a sensor to its autonomous movements. By using the SICK LMS on our robot, we will be able to detect and avoid 2 obstacles with it. Secondly, it shows that GPS and SICK LMS data coupled with onboard cameras can be integrated together to form a guidance system.
Figure 1.1 Vasilius
The second robot is the Centurion I1 shown below in Figure 1.2. This robot uses an interesting frame design and encoders with a 0.5' resolution. They use Lexan sheets as shelving in their design to reduce weight. They also provide good block diagrams of their control system. A web-cam is used as the onboard vision system. Complimenting this system is diffused visible sensors (these aid in the detection of road edges and potholes), electronic proximity sensors, and sonar sensors. This presents an array of alternatives for detection techniques that may be applicable to our project. Figure 1.2 Centurion
The University of Michigan-Dearbom developed an interesting vehicle called
FAST, shown in Figure 1.3. It is a stripped down Power-Wheels toy that was adapted into a mobile robot.
Figure 1.3 Fast 4 This concept is interesting because it offers a simple, powerful chassis to build from. Their paper explains the adaptation of the manual steering found on the vehicle to an electronically controlled steering system necessary for autonomous use.
The University of Florida came up with a Power-Wheels concept as well, it is called Eliminator, seen in Figures 1.4 and 1.5.
Figure 1.4 Eliminator
Figure 1.5 Eliminator (before modification)
This was derived from a Power-Wheel chassis (different from FAST) but they also modified the rear wheels to allow better traction. They modified the steering 5 mechanism in a different way compared to the University of Michigan-Dearborn. This robot also uses the SICK LMS as an obstacle detection device.
The University of Alberta has a unique mobile robot concept. It is called the
Kodiak, shown in Figures 1.6 and 1.7.
Figure 1.6 The Kodiak
Figure 1.7 The Kodiak at a Convention
They also offer the Bear Cub and the Polar Bear (Figures 1.8 and 1.9
respectively), two sturdy looking concepts. Figure 1.8 Bear Cub
Figure 1.9 Polar Bear
The Bear Cub is the first design so far, in this literature review US indepc:ndent drive on each wheel; four independent encoders are used the ~ntrol schem e. This paper (1roogood, 2001) also discusses the frame design r wl the 7 material was chosen. Contained in the paper is a description of the robot and its components
The Polar Bear operates by a hydraulic power transmission scheme. It makes use of an 18 hp engine to drive the hydraulic system which delivers power to each wheel.
In one paper (Arkin, 2002), the results of a SICK LMS used to generate 3D indoor environmental models is shown. See Figures 1.10 and 1.1 1 for the results; the robot with the SICK LMS is shown in Figure 1.12.
Figure 1.10 Georgia Tech Mobile Robot Lab Image of Hallway by SICK LMS
Figure 1.11 Georgia Tech Mobile Robot Lab Image of People by SICK LMS Figure 1.12 Georgia Tech Mobile Robot
The National Institute of Standards and Technology also uses the SICK LMS for obstacle avoidance and 3D mapping (Evans, 2002). In their design, the SICK LMS is mounted on the top of a tower robot and pointed down in a set angle. The robot then moves along and the SICK LMS takes data while moving. The following figures (Figure
1.13 and Figure 1.14) show their set up and SICK LMS generated models.
Figure 1.13 NIST Robot Figure 1.14 NIST Hallway Model
1.2 Thesis Objectives
The goal of this thesis is to present a mobile robot developed for the Avionics
Engineering Center at Ohio University. The objectives of this thesis are:
1. To develop a mobile robot chassis that is expandable for future hardware and
sensor upgrades.
2. Develop and simulate a controller architecture for autonomous operation of the
hardware
3. Choose an array of sensors that will allow navigation in any environment 10 2. Project Background
The goal of RoboCupRescue (http//www.r.cs.kobe-u.ac.jp/robocup-rescue)is to design and build autonomous mobile robots that can autonomously move into disaster locations such as a collapsed building. While in the building, the autonomous robots will then start to search for and find victims while ascertaining their condition. As the robot searches, a map is being continuously prepared and all victims will have their location and condition notated on the map. The robot should also find any hazards that occur along the way, and put these on the map as well. Once the robot has made a map it can then be sent to a human rescuer helping them to locate the victim efficiently and avoid the troubles encountered by the mobile robot.
2.1 Ohio University's Interest
Due to Ohio University's involvement with RoboCup soccer, Dr.'s van Graas and
Williams felt that it would be worth while to build a program for autonomous mobile robots aimed at RoboCupRescue and outdoor use as well. An international competition has been formed for a number of years that includes cooperation and sharing of knowledge.
With the events of September 1 1,2001, coupled with the expert knowledge of the
Avionics Engineering Center and the solid partnership formed by the Avionics
Engineering Center, Electrical Engineering Department and the Mechanical Engineering
Department this development of a search and rescue mobile robot was a logical step for the Russ College of Engineering. Drawing on the resources available, Ohio University 11 can become a competitor in the RoboCup Search and Rescue competitions and outdoor vehicle competitions.
2.2 Our Approach to the Competition
We want to bring to the competition a mobile robot that has solid navigational capabilities. Drawing on the Avionics Engineer Center's expertise we want a mobile robot that can use inertial navigation for guidance and be corrected by the use of a laser ranging device. Most competitors use a laser ranging device for obstacle detection only and use inertial, GPS, or ultrasonic sensors for navigation. It is our hope to initially employ an inertialllaser system that will later be augmented by ultrasonic sensors and bump sensors. However, the goal is also to use the laser ranger as a mapping unit.
The conventional method of map making is to drive around and use some form of obstacle detection (usually ultrasonic sensors) to create a map. This would entail driving a certain known distance and cataloging all obstacles encountered as well as logging their distance from a set point. After this is done, a map would be made of the recorded data.
Instead of using this method, we would drive into an unknown area and halt the vehicle.
The laser ranging unit in this solution can scan in a 180 degree path. We would then rotate the laser ranging unit on a circular arc in an effort to form a spherical pattern around the laser ranger origin on our robot. We would then collect all the data from the laser unit on a hard disk for processing. The data can then be used to produce a map relative to the location of the mobile robot and from this data an image can also be developed. By using the laser ranging unit as a map making device, we can expect distance errors on the magnitude of millimeters. This would be a valuable asset to 12 rescuers who would then have good distance measurements and, if necessary, three dimensional pictures of what they could expect to see.
2.3 NIST Field Overview
NIST (National Institute of Standards and Technology) is a major sponsor of the
RoboCupRescue competition. NIST develops the standard test arenas that the competition uses to evaluate each competitor. The arena created by NIST emulates conditions which may be found in a disaster-struck building. The damage extent shown in the NIST arena can range from mild to severe damage. All competitors of the urban search and rescue genre test their machines in these arenas. NIST has developed mobile arenas that are sent to other countries for use in testing and competitions. Inside the arena are victims that each robot must find to be deemed successful. The victims are both adult and child mannequins that have some real human quality to them. The robots must sense the victims by sight, touch, hearing, or heat. All victims are equipped with heating pads to give the illusion of body heat, some have audio capabilities to enable them to moan or cry for help.
The arena consists of three levels of difficulty. The levels are color coded with yellow being the easiest, orange being moderate and red the most difficult.
Yellow looks like an office that has had a strong wind storm go through it. When a person looks into the yellow section, they will see the floor is covered in paper and trash is thrown through out. There are doors to each room, but they are open or easily moved to an open position. An occasional mirror has been placed in the section to try and confuse anyone who would be looking through a camera and controlling the robot by 13 remote control. Victims are located in the rooms but are not hidden by debris or other trash.
The orange level has an increase in difficulty when compared to the yellow level.
This level has two different floors. The robot is expected to climb ramps with obstacles on them, navigate up or down flights of stairs and to detect and avoid holes in the floor that could possibly allow the robot to fall out of the test arena and onto a net. In this arena, the doors may have obstacles, making access to rooms more difficult. The victims may have rubble on them, making their detection tougher than those in the yellow region.
The orange level can also use compressed COz flowing out of pipes to simulate a gas leak; this increases the amount the robot must rely on other external sensors to detect victims and navigate due to onboard camera vision being obscured.
The red level mimics a true disaster area. The operator of a mobile robot can expect to see bricks and concrete, plastic, construction material, steel fence and pipes in a rubble pile. There are few access points to enter the rubble and the victims are not out in the open. Each robot must use sensors to navigate in or over the pile and search for victims. Items such as milk crates are used to simulate box beams found in buildings.
There is an absence of light from a tarp over this arena. All light must be produced by the robot itself.
NIST uses a new level to separate the winners from the beginners. An old NIKE missile silo from the 1930's located near the NIST grounds in Gaithersburg Maryland has the designation of the black arena. Because the concrete is a few feet thick and the silo houses rooms that are sound proof and blast proof, the testing of navigation will be a challenge. None of these attributes allows much signal power to run through walls. 14 When the silo is sealed, no light or sound is present. Robots hoping to navigate this area must have a great navigation and sensory system. At the time of my visit, December
2002, only marginal success had been shown in the silo by the company iRobot. Figures
2.1-2.4 show the layout of the NIST field and describe the victims found in the arena.
Figure 2.1 NIST Arena 71 Figure 2.2 NIST Arena Diagram
Figure 2.3 NIST Victims Figure 2.4 Victim Description
2.4 Planned Vehicle Use Now and In The Future
The mobile robot of this thesis is intended for use in all NIST arenas. This hardware will be built to have enough power to handle each arena but also be small enough to allow maneuverability throughout the arenas. In designing this mobile robot, the possibility of outdoor use was also taken into account. A robot with relatively high ground clearance, a very strong frame, long-life batteries, and a variety of navigational sensors is required. Whether used indoors, outdoors, or traversing through a hazardous area, this robot must function well. The robot will make use of four independently- 17 controlled, high-torque, high-horsepower DC electric motors. By utilizing independent control of each motor, guidance and obstacle avoidance will be performed. 18 3. Preliminary Design Approach
When considering the task of starting a mobile robotics project, a few options need to be considered. First, can you buy a mobile robot from industry that will suit the needs of the project at hand? Second, if you are able to purchase a mobile robot platform, what kind of access do you have to the robot's computer and controls and can you make the necessary changes to tailor it towards your goals (such as adding required sensors)? Finally, if none of the options above are available, what kind of robot should be built from scratch to best fit the needs of the competition and the goals of the project?
3.1 Overview of Existing Robots
The main aspect noticed when looking at industrial robots is that most are not designed with search and rescue in mind. The design is in a tower format where the robot is taller than it is long and is supposed to traverse flat floors or hallways. For search and rescue applications a robot capable of climbing stairs and rubble will be necessary. This property results in the exclusion of all tower design robots. Some companies do offer some solutions to the problems associated with search and rescue applications.
Angelus Research offers a product called the ART 1 (Figure 3.1). This is a tracked vehicle that is made to traverse many types of terrain. While it is small (7 inches high x 13 inches wide x 22 inches long) it looks good for the small spaces required for a small mobile search and rescue robot. However the design of this robot does not permit the addition of more sensors. The robot comes equipped with videolaudio only. At the time of inquiry, the robot was not for sale. Figure 3.1 ART 1
iRobot is a company that was founded by MIT graduates and currently offers robots for research, industry and the government. For research there are two models that could meet our requirements. These are the ATRV-2 (Figure 3.2) and the ATRV Jr.
(Figure 3.3). The ATRV-2 is a large vehicle: it is 25.6 inches high x 41.3 inches long x
3 1.5 inches wide and weighs 2201bs. While this robot may be able to climb stairs, there is no documentation saying that it can do so. The ATRV-2 can be equipped with multiple sensors including but not limited to ultrasonic, GPS, LADAR, INS, and multiple vision systems. One problem is the base system costs $39,400 and all the above mentioned sensors, except ultrasonic, are extra. For example, the LADAR system (SICK
LMS) costs an additional $8,100 while the same unit can be purchased from a retailer for
$5,470. Figure 3.2 ATRV-2
Figure 3.3 ATRV Jr.
The ATRV Jr. is a smaller version of the ATRV-2. It offers the same sensor packages but costs about $15,000 less than the ATRV-2. It does not offer any information on its ability to climb obstacles.
The Packbot (Figure 3.4) is a new robot from iRobot. It offers good obstacle traversing capabilities but is not large enough to mount any external sensors on.
According to the website, only a few senor options are available. Figure 3.4 Packbot
Applied A1 Systems INC offers one robot (Figure 3.5) that is designed for outdoor search and rescue. Unfortunately is it limited to climbing objects 15cm high and does not offer much room for the addition of sensors that do not come standard
Figure 3.5 GAIA-2
Autonomous Solutions INC offers a nimble robot. The W.A.T.V (Walking
Articulated Track Vehicle) shown in Figure 3.6 can crawl over obstacles due to its design. This design uses four independent tracks that can function as legs. In a video available on its webpage
(http//www.autonomoussolutions.com~research/projects/watv.html),the W.A.T.V is shown traversing a variety of terrains. This design may or may not allow the addition of sensors on it. There are no physical dimensions listed on the webpage. By contacting the company, it is found that the unit will not be available for purchase until it has cleared phase I1 government funding. Figure 3.6 W.A.T.V
Kadtronix is a company that offers parts for mobile robots. They offer a frame
(Figure 3.7) that is made of steel and measures 26 inches long x 23 inches wide x 11 inches high and is driven by four independent motors. The problem with this unit is that the company could provide no details about the motors. When asked what type, power, and manufacturer they only reported 12 VDC with no other information. Also, if this is purchased the unit only comes with the motors and frame, no controllers, cables, or manuals etc.
Figure 3.7 Kadtronix Frame
There are many robots suitable for our needs in the academic realm; however, none of these are for sale. They are mostly custom built and designed from the ground up 2 3 by a team of students at their respective university. This makes for unique designs, and commonly only one unit of each robot exists. Because of this, and the limited scope of industrially-produced mobile robots the decision was made to build our own in-house robot that we could have complete control of.
3.2 Power- Wheels Concept
Upon researching through various competitions (IGVC, RoboCupRescue, etc) many feasible mobile robot concepts arose. One of these is the modification of a Power-
Wheels toy vehicle to a mobile robot vehicle capable of handling heavy weight and offering a long running time. The idea came from searching through the International
Ground Vehicle Competitions (IGVC) archives. A project from the University of
Michigan (FAST A Fully Autonomous Smart Transporter http//www.igvc.org/deploy/design/reports/dr13.pdf)showed the modifications necessary and what types of equipment the Power-Wheels chassis could handle. I decided to investigate this and see what it would take to make a mobile robot from one of these toys.
When looking at the chassis, there is ample room to place electronics as these toys were made to carry two children (age 6 and with 1301bs gross weight combined). Figure
3.8 is a picture of the toy followed by the chassis in Figure 3.9. Figure 3.8 Power-Wheels Toy Car
Figure 3.9 Chassis Schematic of Power-Wheels
Because of the 1301b payload, many types of sensors, computers or batteries could be carried by this toy. The chassis offers multiple mounting options for laser rangers, thermal cameras, ultrasonic sensors, inertial and GPS units. Any of the fenders would be good mounting locations for sensors that need to see out of the vehicle. The 25 front grill area could be modified to handle cameras or laser ranging units. The rear body rails could be used to hold antennas, cameras, ultrasonic sensors or other devices.
The floor space would be used to hold batteries and a computer. This vehicle also has seat belts that could be used to secure components.
This toy comes standard with a 12 VDC deep cycle battery and charger. The battery is stored in the front compartment and is noted by "5" in Figure 3.9. The battery is strapped down so it will not move. Two 12 VDC motors power this car. Each motor drives one rear wheel. The speed options are 2.5 and 5 mph forward and 2.5 mph in reverse. An automatic brake comes standard as well. The range in speed and automatic brake are desires for any mobile robot. This would enable slow speeds when searching for victims and give the freedom of traveling at higher speeds when roaming from one location to another. Having seen these and formerly having one, the motors are encased in a tough plastic shell, this protects them, helps keep them clean and dry, and adds to ground clearance.
The drawbacks of using a toy as a mobile robot quickly become apparent when thinking about the environments that a search and rescue mobile robot may encounter.
Since plastic makes up nearly the entire toy, the focus should be there first. The plastic is built to withstand children but mounting sensors to it and having to secure these sensors through the use of bolts or straps may fatigue the plastic in such a manner that it was not designed to withstand. This would not be known until a fender or some other part failed.
Heat becomes a major concern when dealing with collapsed structures. If the robot were to encounter a fire, there is the possibility the toy could melt or be weakened to the point of failure. One of the biggest concerns is how the toy would respond to 2 6 shock. With custom designing a frame, we can tell how much stress the frame can handle. So if we plan to carry 2751bs of weight we can design for a maximum of 14001bs with no harm to the frame. With this toy, the actual limit is unknown. If the toy were to fall through a hole in the floor or endure some other shock loading, there is no way to ascertain whether the vehicle could withstand this. The issue of a motor coming loose or failing is a concern. Finally, the plastic wheels would be unsuitable for gripping certain surfaces needed to be overcome by a search and rescue mobile robot; this is also reinforced by the fact that the toy is two-wheel drive. Because the wheels are a hard plastic with little tread, loose surfaces that were on an incline would hamper them. Also, with the weight of the battery towards the front of the vehicle, this would produce a push
(not pull) motion. That makes for a non-ideal traction scheme.
A steering device would have to be implemented before this could become a mobile robot. While humans can easily turn the wheel, a motor with a controller would need to take the place of a human. According to the University of Michigan this is not an easy problem to solve (http//www.igvc.org/deploy/desigdreports/dr13.pdf).
It is my belief that the Power-Wheels concept would not make a suitable candidate for an urban search and rescue mobile robot. Due to size, traction, and certain unknown attributes there are too many failure modes to allow this vehicle to succeed.
However, for an outdoor environment (where it can be reasonably assumed no heat, falling, or very steep inclines with loose surfaces) this is a good choice for search and rescue autonomous vehicle, and it should be noted they are very cost effective, selling at
Walmart for $200-$275 depending on the model and age group it is intended for. 3.3 Arm-Linked Robot Concept
Upon visiting NIST in December of 2002 and gaining first hand knowledge of the
RoboCup Search and Rescue arenas, I started trying to think of what type of robot could be designed to search through rubble piles and climb over obstacles. I determined that it might be effective to design a robot with two bodies connected by a robotic arm.
The first item was figuring out what kind of body would be needed to run this type of system. The robot would have to be reversible, meaning that if the robot were to fall on its back, the controls and drivetrain become reversed and it keeps going. This means the body must be under the reach of the wheels or tracks and it must be tough if it is to be able to handle falls. The easiest solution was a body that utilizes tank tracks. The tracks could be on wheels that were taller than the chassis giving the desired capabilities for overturning. The tank track was chosen for four reasons. Fewer motors arc needed to drive the robot. One per track is needed rather than four (for a four wheel drive robot).
The tank tracks eliminate the need for a steering mechanism. Turning can be done by stopping or reversing one motor while the other drives forward or in the opposite direction. This leaves more room inside for equipment. Also, the tank track removes the need for the many wheels that would be needed to keep from bottoming out and getting stuck on the edge of a stair or corner of a beam. In addition tank tracks help keep debris such as chunks of concrete, slivers of wood, or pieces of steel from lodging in between the tires and halting the vehicle. The designed body is shown in Figure 3.10. Figure 3.10 Robot Body Concept
The design of Figure 3.10 has a 3" wheel height and is 9" in length. This can enable enough room for batteries and sensory equipment as long as they are not bulky or power hungry.
The second major design issue is the arm that will attach to each base and serve as a maneuverable link. It should allow the two bodies to move against themselves in a manner that will be beneficial to climbing rubble and obstacles when searching for victims. Due to power considerations, the arm should be controlled by as few motors as possible in order to allow longer operational life under search and rescue conditions. The arm must be lightweight yet strong. Movement must be constrained to allow the body to rotate about the arm when making turns. The arm should have some flexibility to allow it to be off center from the body when maneuvering under low objects or tight turns. A picture of the arm will help explain these needs (Figure 3.1 1). Figure 3.11 Arm
The yellow object is the arm. The red disk is a bearing that will allow the arm to rotate around the center of the robot chassis. The green crescent shape is a guide that will allow the arm to rotate up and down (+90,-90). The grey object with a copper colored disk represents the arm control motor. Because the body will rotate about the arm a bearing will be placed on the bottom part of the arm where it is attached to the chassis.
The motor will be used to keep the parts of the arm inline when maneuvering. The following CAD models in Figures 3.12- 3.16 depict the use and implementation of the arm on the body itself. Figure 3.12 Body with Arm Attached
As seen in Figure 3.12, the amwill have control in every direction. This will allow the arm to enable the machine to overcome many obstacles. As shown here, the arm will move *90° and be able to rotate to the sidewalls of the chassis. The given parameters will ensure that in the event of a rollover the machine will be unaffected and continue on by reorienting the arms.
The joining of the two bodies shows the summary of this design concept (Figure
3.13). Figure 3.13 Bodies Connected
Figure 3.13 shows the two bodies connected by a top bar that will be used for lev,erage. The length of the arms and bar has yet to be determined because it will depend on the size of the objects the robot is trying to overcome. One thought has been to install tellsscoping arms that would extend or contract to the necessary lengths. In Figures 3.14-
3.16 the robot is working its way up a standard set of stairs. Figure 3.14 Beginning to Climb
Figure 3.15 Climbing Figure 3.16 Continuing to Climb
As seen in Figures 3.14 - 3.16 the robot looks interesting, conceptually speaking.
However, it had some drawbacks that could not be overcome.
The success of this robot depended directly on its size. Because of the arm, the chassis for each car had to be small and compact. In order to go above or under obstacles a balance had to be found between length of the arm and motors driving the arm as well as the vehicles size. The longer the robotic link and the larger the vehicles, the less maneuverable the unit would become in tight spaces because of either length or height depending on if the arm was up or down. However, if the arm was large compared to vehicle size, then weight and balance become a problem.
The biggest challenge to this design was the sensors it needed to carry and where it was going to carry them. The low profile dictated by this design limited the payload capacity to ensure that in the event of a rollover, the operation of the unit could continue unobstructed. This ultimately led to the dismissal of this design.
The number of motors needed was a minimum of six (two per vehicle and at least two for the operation of the robotic link). Assuming that these are all 12 VDC motors with a high torque, we see that the power requirement is high. Including the navigation and sensor system, and the need to keep their power system separate, battery weight and size becomes an issue.
Another element that excluded this design was the SICK LMS 200 laser ranging device shown in Figure 3.17.
Figure 3.17 SICK LMS 200
This device measures 8.3 inches high x 6.1 inches wide x 6.1 inches long with a power requirement of 24 VDC and 20 watts. The power needed by this device combined with its size led to the rejection of this design. There is no way to keep a low profile when using this laser scanner. If the design was scaled up to properly handle the SICK
LMS 200 and its power requirement, the robotic arm would be too big and cumbersome to allow fine motions in confined spaces. 3 5 4. Final Design Approach
Throughout the course of looking for suitable robots available for purchase, it was found that there were none. Robots that were deemed suitable had to be reasonable in cost, allow access to all software and hardware, have the ability to carry additional sensory components, and be robust to allow operation in various environments. Because of the lack of robots with all of our requirements, the market made building a search and rescue mobile robot the only option. When considering what approach to take for designing and building a mobile robot, considerations of weight, size, ability to be expandable (addition of more batteries, sensors, etc) had to be taken into account. The most efficient way to evaluate all of these properties is to use solid modeling software to evaluate different designs.
4.1 Mechanical Design
When working out the mechanical design, three main components will determine the success of the robot. They are the frame that will be the base of the robot, the motors that will power the robot, and the tires that will allow the robot to travel in various environments. If any of these items are undersized or weak, the robot will fail.
4.1.1 Frame Design
For mobile robot design, a frame with a high strength-to-weight ratio is desired.
Aluminum is a suitable choice because it has a high strength-to-weight ratio and is easily machined. Different aluminum alloys offer different properties for strength-to-weight ratio. A Solid Edge model of an Aluminum 606 1-T6 frame is shown in Figure 4.1. 36 Aluminum 6061 -T6, shown in Figure 4.2, was chosen because it has very strong
structural properties and is widely available. Square bars were chosen to construct the
frame, with each structural member measuring 2" x 2" x 0.25". This gives strength and a
large surface area for mounting hardware. For the initial frame, a rectangular shape with
cross members was chosen as the design. This was to yield a rigid base and be easy to work with. The frame will be 26 inches long, have a width of 18.5 inches from outside to
outside with a thickness of 2 inches. This frame was modeled using Solid Edge and
evaluated using Algor and Visual Nastran. The results of the modeling and evaluation will be seen later in the chapter.
Figure 4.1 Aluminum Frame Figure 4.2 Aluminum 6061-T6 Structural Members
Unfortunately, the aluminum frame will not be available for sometime due to the
Ohio University machine shop's backlog of work. To remedy this I, along with my uncle
George Mark, constructed a welded steel frame for use and testing. This frame is made out of 1.5" x 1.5" x 3/16" carbon steel 90" angle. It is the same length and width as the aluminum frame, but differs in thickness and structural member shape. As with the aluminum frame, the steel frame was modeled and evaluated using Solid Edge, Visual
Nastran, and Algor; the model and results of these tests will be seen later in the chapter. 38 4.1.2 Motor Sizing
The next major design issue is motor sizing. Motors for a mobile robot must have high power to allow movement in a variety of terrains and on inclines as well as be efficient and lightweight. The motor chosen is shown in Figure 4.3, the NPC-T64.
Figure 4.3 NPC-T64 Motor
The first item when consider when choosing motors is their operational environment. Because our environment will be varying depending on the type of disaster we needed a robust motor that is capable of handling different environments. The gearbox on this motor is constructed of 6061-T6 aluminum. The mounting points for this motor are on the gearbox and according to NPC the T64 motor can withstand a static load of 3501bs. The shaft and gears of the motor are constructed of steel and offer a 20: 1 reduction ratio. At the end of the motor is an enclosure. This enclosure is constructed of aluminum 6061 -T6 and is intended to be used as an environmental enclosure for feedback devices such as encoders.
The second important property of these motors is the power consumed versus the power output. This type of motor is a 24VDC (12 or 36 VDC optional) permanent magnet motor that fits into our desired electrical system and weights only 71bs. In Figure
4.4, shown below, the dynamometer test results for this motor are shown. 1825 1 110 1 STALL 1
Figure 4.4 NPC-T64 Dynamometer Results
The motor chosen was to have enough power to start from a stalled position on finished concrete at an angle of 45". The estimated weight of the robot is 275 lbs.
Calculations show that the stall torque needed to move a 275 lb mobile robot on a 45" incline made of finished concrete would be 194.5 in-lbs. Figure 4.5 illustrates this situation. Figure 4.5 Dynamic Model
In this case, the total weight of the system (275 lbs) has been distributed evenly over each wheel resulting in a net weight of 68.75 lbs at each wheel. Three unknown forces are shown, the weight in the x direction (F,), the static friction force (Fs), and the normal force (N) with the assumed value for static friction (p,) equal to 0.8. The stall torque of the system can be found by finding the necessary forces using statics.
F, = 68.75cosa (4.1)
N = 68.75 sin a (4.2)
F, = P,N (4.3)
Solving these equations we obtain the forces.
F, = 68.75 cos45" = 48.6 (lbs) (4.4)
N = 68.75 sin 45" = 48.6 (lbs) (4.5)
F, = 0.8(48.6) = 38.9 (lbs) (4.6) 4 1 The calculations shown above tell us that the stall torque needed to be applied is the radius of the tire times the frictional force and that the force needed to be overcome to allow acceleration is the motor force minus the static force and x direction weight force. The following equations will show this.
T, Motor Torque Ts Stall Torque R, Tire Radius F, Force of Motor M, System Mass Asy, System Acceleration
Solving these equations we find the following values.
T, = 5(38.9) = 194.5 (in-lbs) (4.10)
In equation 4.10, the required stall torque is found to be 194.5 in-lbs. This is found by multiplying the radius of the tire by the amount of friction force where the tire and concrete meet. This torque translates back to the motor through the wheel. The motor must be able to output this much torque to overcome stall. The motor force is found in equation 4.11. Motor force is the force generated by the motor and is found by 42 dividing the torque of the motor by the radius of the tire. By comparing the force of the motor with the weight force it is possible to solve for the acceleration based on
Newton's laws. The acceleration calculated in 4.12 is found to be 9 ft/sec2, this acceleration may seem high but it is not continuous and will end when the motors reach their maximum speed of 4700 rpm on the armature (235 rpm on the gear head). If all four motors are outputting their maximum torque and force then they each overpower the force and torque seen at each wheel. However, if only one motor were operating, then the required torque would be 777.8 in-lbs and the required force would be 194.5 lbs.
This, coupled with the resistance of the other three motors would not allow the robot to break stall on finished concrete at a 45' incline.
4.1.3 Tire Determination
Tires play an important role in the capabilities of the mobile robot. Tire tread pattern, size, and style are all factors for selecting a proper tire.
The pattern of a tire will directly relate to the functional capabilities of this robot.
Because this robot will see indoor action and also be required to maneuver over rubble or operate outside at times, a pattern that could handle all environments was chosen. The tread pattern found on our tire is diamond, shown in Figure 4.6. This pattern allows easy movement outside because it can grip well. Figure 4.6 Tire Tread Pattern
The size of the tire can affect the amount of force on the ground and the torque of the motors. A tire size of 10 inches in diameter and 3.5 inches in width was chosen. This worked well both indoors and outdoors but was undersized when stair climbing was attempted. As a solution to the stair climbing problem a new tire has been selected. This tire has a diamond style tread pattern, is 14 inches in diameter and is 4.5 inches wide but has not yet arrived. Because of the overall strength of the motors is so great when compared to what is needed for robot motion, tire size changing does not negatively affect the robot. It should be noted that larger tires will put less force to the ground but the same torque when compared to smaller tires.
The third important factor in tire selection is solid core or tube. Solid core tires were chosen as a way to offer a more rigid tire, maintain strong contact with the ground 44 and to avoid a flat tire. The ability to avoid a flat tire is a must in search and rescue mobile robotics because it is not know what debris will be found in a disaster area.
4.1.4 Solid Edge, Algor and Visual Nastran
Designing of the mobile robot relied heavily on computer aided design (CAD) programs. Three were used, Solid Edge, Visual Nastran, and Algor. These programs were used to draw the robot to scale and to test its strength to loading and torque from motors.
Every component was drawn in Solid Edge and then imported into Algor, Visual
Nastran or both. Models of the SICK LMS 200, motors, sensors, batteries, wheels, etc. had measurements taken by hand or from technical documents and then drawn to scale in
Solid Edge. This was used to see relative size between components and identify unforeseen problems, such as battery space on the frame and the interference mounted motors could cause. Color was assigned to each component for realism.
By placing all of the components together and using tools in Solid Edge, an accurate picture of the mobile robot can be generated. This is helpful when trying to decide where to place sensors and how high to mount the SICK LMS sensor. For the mobile robot of this thesis, please refer to Figure 4.1 and then see Figure 4.7 and Figure
4.8 for a demonstration of the evolution of a Solid Edge model. Figure 4.7 Frame with Motors
Figure 4.8 Aluminum Frame, Motors, Tires, Batteries and Controllers
Figure 4.1 is a Solid Edge model of an aluminum frame. Each member is a square aluminum rail with holes cut out to simulate bolt holes that will be used for mounting hardware. Each rail has been rigidly fixed so that Solid Edge and other CAD programs would see this as a welded or solid frame. It should be noted, that the short 46 cross members are in the form of a hollow square rail as well, they are not solid. The second figure, Figure 4.7, shows how the fame will look once motors have been attached
Information can be obtained from this model, such as necessary frame size to accommodate the motors. Each motor has been rigidly attached to simulate a stiff bolting pattern. In Figure 4.8, four twelve-volt deep-cycle batteries as well as models of the
Roboteq motor controllers have been placed on the frame in order to see their size relative to the frame and determine their layout. While not demonstrated in the figures,
Solid Edge does have the ability to measure distance between objects. An example of this would be the distance between the backs of facing motors (2.5 inches) or the distance between the batteries (changes upon different configurations). This information will allow the frame to be adjusted to ensure the best fit of all components before it is produced physically.
Figure 4.9, shown on the next page, is the carbon steel frame. Dimensionally it is representative of the desired aluminum frame. The holes shown in the picture are bolt holes used for mounting the motors as well as hardware. Figure 4.9 Carbon Steel Frame
Both Visual Nastran and Algor were used as FEA (Finite Element Analysis) programs to evaluate the model (in this case both frames). Algor was used to evaluate a pressure load applied to each frame. The eight bonding points (fixed points where the frame is held in every direction) are the four holes in each long frame rail. Please see
Figure 4.1 and Figure 4.9 for a view of their location. A uniform pressure of 6psi was applied to the entire surface area of the aluminum frame; this pressure is to simulate a large load of 1400 lbs evenly distributed across the frame. This was chosen for two reasons. First, with the estimated final design and fully equipped weight at 2751bs, the robot should never weigh more than 3001bs with the addition of some sensors (batteries add the largest amount of weight and are considered in the final design estimated weight); this makes for a factor of safety of 4.6. Secondly, the motors were given a static load of
3501bs in their testing (obtained from NPC); our design uses 4 of them, so evenly 48 distributed weight could total 14001bs to reach the motors theoretical limits. In Figures
4.10 and 4.1 1 the resulting stress and displacement of the frame as calculated by Algor to a 6psi load is shown.
Siren won Yises Ibf(inA2)
Load Case I of I Maxlmum Value 151 3 16 Ibf/(lnA2) Mlnlmum value I6 7535 Ibf/(rnh2)
Figure 4.10 Stress of Aluminum Frame at 6psi Uniform Pressure Nodal Dtsplacement Z Component In
Load Case' 1 of 1 Maximum Value, 1 20782e-005 In Mlnlmum Value -0 001 02003 In Figure 4.11 Displacement of Aluminum Frame in Z direction
The carbon steel frame was loaded at lopsi. This still simulates a load of 1400 lbs evenly distributed across the frame. However, there is less surface area on the carbon steel frame when compared to the aluminum frame. Because of that, the applied load pressure is greater. Figures 4.12 and 4.13 show the Algor test results for stress and displacement of the carbon steel frame when loaded at 1Opsi. Stress won Mises I bf/(inA2)
Load Case: 1 of 1 Maximum Value. 751 1 .I Ibf/(inn2) Minimum Value, 61.8325 Ibf/(inh2) Figure 4.12 Stress of Carbon Steel Frame at lopsi Uniform Pressure Nodal Displacement Z Component in
Load Case. 1 of 1 Maximum Value 0.0047017 in Minimum Value -0.000238835 in Figure 4.13 Displacement of Carbon Steel Frame in Z Direction
As seen in Figures 4.10 and 4.1 1 the aluminum frame is strong. The largest stress concentrations are found at the fixed points in Figure 4.8. These are noted by the yellow areas and are 15 13.16 1bs/in2. This is far below the maximum for aluminum 606 1-T6
(maximum yield stress for aluminum 6061-T6 is 35,000 pounds per square inch). The maximum displacement in the downward Z direction is a small 0.001 inches in the center of the frame (notated by dark blue). Also, by looking at Figures 4.12 and 4.13 we can see that the carbon steel frame is strong as well. The maximum stress is 75 1 1. lpsi located in the bolt holes. The maximum displacement in the downward Z direction is .0047 inches, acceptable for any application. The yield stress for the steel in this frame is 48,000psi. 5 2 Based on these results, the combined weight of the frame, motors, and all sensors (including batteries) totaling less than 3001bs, should never pose a problem to the robot when using either frame. The over-designing of each frame is intended to allow modifications that might increase the weight as more is required from the robot.
Visual Nastran was used to evaluate point loading and applying torque to a body.
This is useful for seeing the effects of a single component sitting on the frame (instead of all components) and to predict how the frame might react to motor torque. While Algor can do point loading, it is not able to due torque evaluations. In the following pages test results from Visual Nastran are shown. The loading shown is an attempt to model what could happen to the robot through the course of its operation and to try and find weak points in the design.
Figure 4.14 shows the reaction of the aluminum frame to an eight-hundred inch- pounds of torque load applied to the front left and front right of the frame in the positive y direction. The red arrows in the picture represent the placement of the loads. This was chosen to simulate the position of the motors. The back of the frame was fixed rigidly in all directions (shown by the blue stars at the rear of the frame) to see how two motors would flex the frame. zn M~sesStress (PSI) Figure 4.14 Torque Applied at Front, Rear Fixed
Figure 4.15 shows how the aluminum frame reacts to two motor on the same side outputting eight-hundred inch-pounds of torque when the rear of the frame is fixed. This was done to see if any effects would be detrimental to the frame if by chance the robot was only operational on one side. Torque A
Max Valu
von M~sesStress ( ps~) Figure 4.15 Torque Applied to Right Side, Rear Fixed
Figure 4.16 shows how the frame would react if it was pinned in the rear and all four motors were outputting maximum torque (eight-hundred pound-inches). It should be know that while is cannot be seen, two more torques are applied to this frame on the other side of the frame in the same location as the visible two (red arrows show position). As seen in all figures, the frame, can withstand the torque output of all the motors without being damaged by overstressing. -&M3inlb Torque A
Max Valu~
von M~sesStress (PSI) Figure 4.16 Torque Applied at Each Corner, Rear Fixed
Figure 4.17 is to represent that might happen if one motor becomes stuck and all other motors run at the maximum torque. The torque from each motor is shown in red, while the fixed portion is representative of the motor on the rear left (facing frame). The two blue protrusions at the rear left of the frame represent bolts holding the frame to the motor which is considered immovable in all directions. von M~sesStress (psi) Figure 4.17 Fixed at One Corner, Max Torque on Other Three
Figure 4.18 is for comparison purposes. When looking at total weight of the system, it should be a maximum of 3001bs (estimated final design weight is 2751bs). This figure was merely to demonstrate that the frame is more than capable of supporting this amount of weight. Note the frame is fixed in the rear and the point load is located in the center of the first cross member. Mar Valul
e+3 e+3 e+3 e+3 e+3 e+3 e+3 e+3 e+3 e+3 e+3 3001b Point Load e+3
von Mises Stress (psi) Figure 4.18 Point Loading, Fixed in Rear
The carbon steel frame was evaluated in much the same manner as the aluminum frame. The following figures detail the capabilities of the of the carbon steel frame to handle the torque from the motors and point loading.
As seen in Figure 4.19, with the rear of the frame fixed rigidly and the front motors running at hll power, the steel frame is capable of handling the load. von Mises Stress (psi) Figure 4.19 800in-lbs Torque at Front, Rear Fixed
As shown in Figure 4.20, with all four motors running at max power the steel frame will have high stress in certain areas because of less surface area, but as with the aluminum frame, it can handle the power without damage. von Mises Stress (psi) .$ Figure 4.20 All Four Motors Outputting Max Torque
Point loading is shown in Figure 4.2 1. The carbon steel frame can easily handle the proposed maximum weight of the entire robot. The carbon steel frame should allow the full testing of the mobile robot because of its strength and weight. /--- 300 Ibf
Max. Value = 2 2.61 e+4 2.44 e+4 2.26 e+4 2.09 e+4 191 e+4 174 e+4 157 e+4 1.39 e+4 1.22 e+4 104 e+4 87 e+3 6.96 e+3 5 22 e+3
von Mises Stress (PSI) Figure 4.21 Point Loading of Frame
4.1.5 Additional Design Considerations
A few additional design considerations were made after the final mechanical design modeling and FEA testing was completed. Based off of recommendations from
NPC Robotics, motor mounting brackets were added to the carbon steel frame. The material used for these brackets is A36 90" angle steel that is 1.5" x 1.5" x 118". In addition to these mounts, a top was constructed for the frame. This top is hinged by clevis pins and can be opened towards the front or rear. This is to allow easy access to the inside for removal or installation of components such as batteries. Figures 4.22-4.28 will show the mounts and top that has been added to the frame. Figure 4.22 Frame with Motor Mounts
Figure 4.23 Frame with Motors in Mounts Figure 4.24 Bottom View of Frame with CAD Model
Figure 4.25 Complete Frame with CAD Model Figure 4.26 Frame with Top Open
Figure 4.27 Completed Robot with CAD Model IS0 View Figure 4.28 Completed Robot with CAD Model Rear View
In addition to the changes made with respect to the carbon steel frame, the
aluminum frame was modified as well. A pin joint was placed in the center of the frame to allow the front and back to rotate. This will act as a type of suspension system.
However, this frame was not completed in time to allow testing of it. In Figures 4.29,
4.30,4.31 pictures and CAD drawings of the frame and its rotation are seen.
Figure 4.29 Pin Jointed Aluminum Frame with CAD Model Figure 4.30 Frame Rotated With CAD Model
Figure 4.31 Conceptual CAD Model of Frame Rotation with Motors and Tires
4.2 Electrical Design
The electrical power for the search and rescue mobile robot is provided by a
24VDC system composed of three banks of 24 VDC battery systems. The wiring and switches were chosen in accordance with the motors and electronics. Both the wire and switches used are rated far above the system requirements. 4.2.1 Power system
The power system will use a total of six, 12 VDC, 3 1.6 amp-hr, deep-cycle gel cell rechargeable batteries. Four of these batteries are used to power the motors currently the motor controllers. One set of two batteries will be connected in series to form a twenty four volt source, thus forming three sets of twenty four volt sources. Two out of the three sets of twenty-four volt connections will be used to power one pair of motors each. The last connection, to be added later, will be identical to those powering the motors in terms of battery voltage, and style of deep-cycle gel cell rechargeable, but not necessarily amp-hour rating as the electronics will not consume as much power as the motors. The third twenty-four volt system will be used strictly for electronics power.
This will prevent large drains associated with electric motors which could affect the performance of the electronics, such as resetting or harming them by varying or spiking currents.
The wiring used to make the connections between the switches and batteries is 8
AWG machine tool wire (blue wire in Figure 4.32) and is rated for 70 amps at 600VAC.
8 AWG wire was specifically chosen because of its power handling capabilities and because the motor controller uses the same size for power distribution to the motors. The wire used to extend the motor wire is 14 AWG machine tool wire. This wire, 14 AWG, is identical in color (black and red shown in Figure 4.32) and power handling capabilities to that of the motor, which uses 14 AWG, and is rated for 30 amps at 600VAC.
The connections to the switches and batteries are made by ring terminals. These terminals are 5/16 (red and blue terminals in Figure 4.32) inch stud size, insulated and have a rating of 600 volts. The connections that are used to make the extension of the 6 motor wires to the motor controller are formed by twist-on butt splices (blue cylinders shown in Figure 4.32) and are rated for 600volts. In order to make the motor-to- controller connections, insulated butt splices were used. They are rated for 600 volts.
Figure 4.32 Wire, Connectors, Terminals and Fuses
Two main power switches are used, one for each dual motor-powering 24VDC system (the electronics 24 VDC system is not considered a main power system). These switches are push button type, with pull-up for on and push-down for off. They are heavy duty and high power, with a rating of 75 A at 28 VDC. Two fuses are used and they connect the positive terminal of the battery to the positive terminal of the Roboteq motor controller. They are heavy duty, sealed fuses (black boxes with wire leads shown in Figure 4.32) that are rated for 50 A at 32 VDC or 67 A at 24 VDC. 4.2.2 Motor Controllers and Sensors
An initial package of sensors and controllers is being developed for the mobile robot. This package will help in the aid and detection of victims of disasters. To date, encoders, dc motor controllers, the FUTABA T9CAP remote transmitter and receiver system and a SICK LMS laser ranging unit have been selected for the package, with additional units of INS, USB cameras, infrared cameras, GPS receiver, and audio capabilities coming in future work.
Roboteq manufactures the AX2550 DC motor controller which was chosen for this project because of the multiple control options associated with it. In Figure 4.33 the
Roboteq AX2550 is shown. The AX2550 is a digital motor controller that can drive two motors mixed or independently. It is programmable and capable of receiving commands from a remote control system or from a computer such as a PC- 104. It has power settings that allow the user to set the amount of current delivered to each motor and it enables the monitoring of battery voltage, current and internal temperature. This particular motor controller is capable of open or closed-loop control. It uses external feedback devices such as a potentiometer or tachometer for closed-loop control. Encoder inputs and software modifications have been developed for the AX2550 for use in closed-loop control. The AX2550 also has the ability to deliver high power. This unit is intended to be used with DC systems of 12 to 40 volts and has the capability to deliver 120 amps per channel for 15 seconds and 80 amps per channel continuously. Figure 4.33 Roboteq AX2550
Encoders were adapted to the NPC-T64 motors for closed-loop control in conjunction with the Roboteq AX2550. Optical encoders from Renco, shown in Figure
4.34, were chosen for our project because of their standard properties and small size.
They offer 500 pulses per revolution, adapt to a 0.25 inch shaft, use RS422 for communication, and are powered by 5 VDC. The encoder's settings are industry- standard; this was chosen to allow a quick replacement should an encoder fail. Figure 4.34 Renco Optical Encoders
The Futaba 9CAP transmitter-receiver system was the package chosen to operate our robot by remote control. This system is for model airplane use, but is adaptable for groi~nd-based applications. The 9CAP is shown in Figure 4.35 Figure 4.35 Futaba 9CAP Transmitter, Receiver, with Battery and AX2550 Harness
The main advantage of this system is that it is programmable, allowing channel mixing. This enables multiple outputs on the receiver to respond to one command from the transmitter. This is especially helphl when using dual Roboteq AX2550 controllers in skid-steer mode. By using multiple outputs on the receiver you can ensure that both controllers receive the same inputs. This is done by having, for example, channels 2 and
6 of the receiver responding to the throttle input of the transmitter. In this case, plug the channel 1 port of one Roboteq AX2550 into channel 2 on the receiver and plug the other
Roboteq AX2550 channel 1 into channel 6 on the receiver. By doing so, both controllers 72 will receive the same command from the transmitter. A significant feature is the programming of the failsafe mode. The Roboteq AX2550 will follow the failsafe command sent by the transmitter in the event of interference or loss of signal. For the
FUTABA T9CAP the failsafe mode has been set to null all outputs and set all commands to zero thus effectively shutting down the controllers if signal loss or interference occurs.
This will prevent uncontrolled operation of the motor controllers which could cause harm to people, the environment, or the robot itself.
The SICK LMS 200 laser ranger is a major component of our robot. It will be used for obstacle detection and mapping. This laser ranger is capable of scanning 180" and obtaining x,y,z data from its measurements. The SICK LMS 200 does not consume much power: It accepts a 24 VDC connection, and uses 20 watts of power. Data is sent via serial port (RS232) to a computer. Please refer to Figure 3.17 for a picture of the
SICK LMS 200.
The make and model for the INS unit, USB camera, infrared camera, PC-104,
GPS receiver, and audio devices are not available at this time. They have not been chosen yet because the primary focus has been to design the power system with enough power for all electronics mentioned so far and enough for the addition of components as they are needed. These devices will be required for autonomous operation, which is beyond the scope of this thesis. 5. Mobile Robot Control
Control of the mobile robot in this thesis is done by human-directed remote control with an emphasis on moving towards closed-loop autonomous control in the future by use of a micro computer or wireless LAN. It should be stated though, that closed-loop control will be dual purpose navigation control is the primary goal with system monitoring being the second goal. That is to say closed-loop control of the robot is the primary goal and utilization of the AX2.550'~ability to monitor voltage and current used by each motor as well as overall electrical system voltage to check the health of the robot is the second goal.
5.1 Open-Loop Control
For the initial control system, the human is in the loop and the system is open- loop because the AX2550 motor controllers have no external feedback, as shown below in Figure 5.1. This is done by utilizing the AX2550's ability to use remote control receiver commands wherein the human is the operator of the remote control transmitter.
Essentially, the motor controller will be set for certain operations and constraints, such as limiting current output to 55 amps per channel. This means that control input for the
AX2550 will be set for remote control operation and the channel settings will be turned to mix. The Roboteq motor controller has two channels labeled 1 and 2. When programmed to mix channels 1 and 2, the motor controller will take a specific input from the receiver (channel 3 in our case) and use this input to drive channel 1 and 2 simultaneously and identically. By doing this, the controller will deliver the same 74 amount of current to both channels thus creating the same speed and torque at each motor. Additionally, when programmed to mix channels 1 and 2, the Roboteq AX2550 will respond to a different input from the receiver (channel 2 in our case) that will cause channel 1 to be driven opposite channel 2. This supplies, for example, positive ten amps to channel 1 and a negative ten amps to channel 2. By doing this, the motors drive in opposite directions. With the motors being on opposite sides of the frame, a skid-steer effect is generated to turn the robot.
Ch 1 Input
Figure 5.1 Remote Control Open-Loop with No Feedback
In future work, the modification allowing encoder inputs for the AX2550 will be utilized, as shown below in figure 5.2. The encoder setting is a form of low level closed- loop control that can include or exclude the human. When reading encoder inputs, the motor controller will synchronize the speed of the motor operated on channel 1 with the speed of the motor operated on channel 2 by adjusting the power to each motor as 7 5 necessary. For testing purposes when using remote control mode, the front set of wheels and back set of wheels will not be synchronized with each other. This is because there is no communication between the front controller (driving the front left and front right) and the rear controller (driving the rear left and rear right), as they communicate only with the receiver. Theoretically, all four motors should have the same speed if both controllers are programmed with identical settings because they will be responding to the same receiver output. However, if one motor is timed a little different than its counterpart on the opposite channel, the AX2550 controlling that set of motors will adjust to the power needed to synchronize that set of motors and in doing so will be adjusting the power differently than the other AX2550 controlling the other set of motors.
Input -Feedback Encoder 1
Figure 5.2 Open-Loop Remote Control with Encoder Feedback 76 To combat this issue, eventually all control will be processed through a central computer as depicted in Figure 5.3 on the following page. In this phase, both motor controllers will send wheel speed data to the computer. This will alert the computer to any differences between the four motors and allow the computer to send the commands to the controllers for the speed at which all motors should be driven. By using the
AX2550's ability for independent control, each motor can be driven at a different power level. This will enable synchronous speed for all four motors and controlled general turning.
Input -Feedback Encoder 1
Figure 5.3 Closed-Loop Control Through Computer with Feedback 5.2 Closed Loop Control
The closed loop control for autonomous motion of this mobile robot (shown previously in Figure 5.3) will depend heavily on the navigational system. Initially, the navigational system will be composed of one SICK LMS 200 laser scanner, one inertial navigation sensor and four encoders (one per motor) and a GPS receiver for outdoor navigation.
The SICK LMS 200 laser scanner is capable of delivering distance data. The premise will be to enter a door way and let the laser scanner map the room. This will serve two purposes. First an accurate picture of the room will be generated as shown in,
Arkin (2003). By creating a picture of the room we will not only have the chance to visually see what is in the room, but also to know the distance to what can be seen in the picture. The knowledge of distance-to-object will be a factor needed to allow autonomous operation in unknown environments.
By having the distance-to-object data, we will be able to complete the second phase of the autonomous operation. This will be the localization of our robot with respect to the room which it has entered. Relying on the SICK LMS data, self localization and calibration of the inertial unit will be possible. SICK LMS data will be used to align the inertial unit to the room. As the inertial unit drifts, corrections can be made by knowing our position relative to the room. This will useful in telling rescuers exactly where in the room they can expect to find victims or hazards because the distance supplied to them will be based from an object, such as a wall, in the room.
The inertial unit will be the input that the encoder readings are coordinated with.
By monitoring the inertial unit it will be possible to know the path on which the robot is 78 on. The inertial unit will alert the robot to any drifting from the desired course. By having independent control of the robot on a per wheel basis by use of the encoders, the necessary adjustments needed to steer with precision and stay on course will be available.
The optical encoders chosen have 500ppr (pulses per revolution). When coupled with the Roboteq AX2550 it will be possible to measure wheel speed, distance traveled, and with an accurate navigation system, wheel slippage. By knowing the distance to objects based on the SICK LMS data and having precise control over the robot, we will be able to navigate in and around obstacles with good knowledge and control of the robot motion and speed.
The Roboteq AX2550 has the capabilities necessary to monitor the main power system and its condition. The AX2550 can monitor a variety of parameters in accordance with the function of the motors. It is possible to monitor power used by the motors, amps used by the motors, battery voltage, and internal temperature of the controller itself.
By monitoring the power and current usage of the motors, we will be able to watch their behavior and detect problems. If one motor starts to act erratic or consume more power than another we will be able to know it in real time as the problem starts to occur. It will also be possible to derive how much torque is being delivered by each motor by monitoring the voltage and current consumed by each motor.
By monitoring the system voltage and power consumed by the motors we should be able to estimate how much life is left in the batteries and avoid running out of energy while in the field. This could be accomplished by watching the currents drawn by the motors. If the currents are deep, such as would be the case in hilly terrain where more power is needed to move the robot, we could cut the runtime down to keep from running 7 9 out of power. If we are on smooth terrain with a stable current draw a longer run time can be allowed.
5.3 Controlled Motion
Precision steering of the mobile robot will utilize closed-loop control. Since there are no turning wheels such as in an automobile, the robot must use the skid-steer technique defined in this thesis as turning-on-a-dime, comparable to that of a tank turning in a circle. The robot will also employ differential steering to allow it to turn while in forward or backward motion. In the following Figures, 5.4 and 5.5, graphical representations of skid-steering and differential-steering are shown respectively.
w~~rectionof Travel WRlghtSide Dlrect~on,Same Speed as Left Slde LeRSlde Dlrectlon, Same Speed as R~ght
Figure 5.4 Skid-Steering CI Same Direction Set Speed C Same Direction Less Speed
Figure 5.5 Differential-Steering
The skid-steer function needs closed-loop control for optimal operation. In skid- steering one side of the wheels rotate in the opposite direction of the other side, as notated by the green and red arrows. This produces a zero turning-radius. However, problems can occur if wheel speed is not the same on all four wheels. In open-loop control mode all four wheels do not turn at the same speed, the cause for this is unknown.
However, the effect it generates is easily identifiable on carpet. While skid- steering on carpet in open-loop control mode, the robot attempts to hop and shake while turning. As the robot is rotating, not all the wheels are turning at the same rate; this causes some wheels to bind on the carpet, because they are being pushed or dragged depending on the direction of the turn. Because of this, the robot shakes or hops. This does not occur on linoleum, smooth concrete, or grass because the wheels are able to easily slip when compared the slipping found on carpet (negligible). The binding of the 8 1 wheels on the carpet can cause navigational problems due to vibrations in the robot that could introduce error into the inertial sensor and also environmental damage based on possibility that the robot could ruin the carpet by grinding its tires into it.
Closed-loop control will mitigate much of the open-loop problem when attempting to skid-steer on carpet. Having all four wheels in synchronous motion will eliminate the force trying to slide some wheels and drag others, which is the cause of the shaking and hopping effects. With all wheels turning at the same speed there will not be as much binding and there for less damage to the floor upon which the robot is turning.
And because of less binding there will also be less vibration in the robot which will reduce the effects on the navigation system, specifically the inertial unit.
As mentioned above, skid-steering is turning-on-a-dime. There is no forward or backward motion of the robot turning center in skid-steering. In order to turn while moving and not stop to make a turn, we can use differential steering. For example, the encoders will synchronize the speed of the wheels while driving forward, please refer to
Figure 5.5, and then to make a right hand turn, the wheels on the right side of the robot will have their speed decreased by a specific amount as indicated by the green arrows and smaller green arrows. The amount of speed decrease will directly affect the turning angle. Finally, to resume a straight path, the left side will have their speed increased to that of the right side. This method of steering will make path corrections while traveling easier and more efficient than having to stop, adjust, and then proceed again. 82 6. Results
The mobile robot in this thesis was evaluated on a performance basis. Velocity and acceleration were measured on grass and brushed concrete. The stair climbing ability was not tested since the new 14 inch tires did not arrive in time for testing. Drift was measured and turning ability (skid-steering and differential-steering) was compared on grass, brushed concrete, and linoleum. Slipping was noted and motion with encoders was compared with motion using no encoders. Video of the robot's performance on grass and concrete was taken and used to evaluate of the robot. The software used to examine the video footage allowed stepping of the video by increments of 0.1 seconds. All starting times were measured from the first frame showing motion. For instance, when measuring acceleration, the time chosen as the starting point (time equal to zero) of acceleration is the time at which visible movement of the robot is first present on film.
The general physics equation shown below in Equation 6.1 was used find the acceleration and velocity of the robot.
D Distance traveled by the robot Do Starting distance already traveled by robot vo Initial velocity of robot 1.1 Constant velocity of robot a Constant acceleration of robot t Time
1 D= D, +v,t+-at' (6.1) 2
There are two phases of evaluation for the robot. The first phase is constant acceleration with linearly increasing velocity. The second phase is constant velocity with 83 no acceleration. When finding acceleration, both Do and vo go to zero. The starting distance (Do) is zero because the robot front wheels are on the zero-distance marker when the trial begins. Also during the constant acceleration phase, initial velocity (vo) is zero because the robot is accelerating from rest. Equation 6.2 shows how the above physics equation (6.1) simplifies when the initial distance and velocity are set to zero.
In Equation 6.2, D is the distance traveled and is found by video analysis, t is time measured from the video in increments of 0.1 seconds.
For the second phase, finding constant velocity, we assume that we have reached constant velocity and acceleration is now zero. Initial distance (Do) is set to zero because constant velocity will be measured from one distance marker to the next. During constant velocity a distance marker will be deemed the zero point and another distance marker will be declared the end point, the value D will be the distance between these points and time will be found by using the video to determine how long it took to travel from the defined zero point to the defined end point. Equation 6.3 shows the simplified constant velocity equation.
D = vt (6.3)
By solving this equation for v we are able to find the velocity when acceleration is zero.
6.1 Velocity, Acceleration, and Braking
Velocity and acceleration data was compiled by running the robot on two types of terrain (grass and concrete). This was done by marking off a set distance, 15 yards by increments of one yard (white marks in Figure 6.1 shown on the next page) in the grass 84 and 30 feet in increments of 6 feet (noted by the concrete joints in Figure 6.2 shown below) on the brushed concrete, and videotaping the robot with a digital camcorder.
Figure 6.1 Grass Field with White Yard Marker
Figure 6.2 Concrete Pad with Joints 6ft Apart
The difference in distance used on concrete and grass comes from the settings where the trials took place. The grass trial took place at my house in Chillicothe, Ohio where a wide open field was available. The concrete trial took place at Stocker Center where a 30ft patch of concrete formed from 5 pads of 6ft in length is available outside the
0 15B lab. As a comparison point, the no load speed of each 10 inch tire should be: 235rev 1min n-(loin) l.ft 10.25,ft -, -* ,-- - = 7mph min 60sec rev 12in sec
On the grass it was more difficult for the robot to accelerate steadily; please see
Table 6.1 for the data. The wheels would slip when attempting to accelerate in a fast manner. This hampered the robot's ability to stay on course and caused the robot to accelerate rapidly because when the wheels did get a grip they were at their maximum speed. The measured acceleration on grass was found to be 14.8ft/sec2. The acceleration found for the grass trial is not accurate. Because the wheels slip, it is very difficult to find the actual time the robot started trying to accelerate. This will cause errors when trying to determine acceleration of the robot because time is not precise.
Velocity found on the grass surface was determined in two ways. It was first measured as a constant velocity starting when the robot was no longer accelerating. The time at which the robot was no long accelerating was determined to be the point at which the time to travel one yard in distance did not change. For example, in Table 6.1 trial two, the time to travel from 6ft to 9ft took 0.3 seconds and to travel from 9ft to 12ft took
0.3 seconds as well. Therefore, it was considered that the robot had stopped accelerating at the 6ft marker and velocity measurements could be taken over the 6ft to 45ft data span.
This velocity was calculated and averaged from three trials and found to be 9.9ftlsec or
6.75mph. Velocity was then measured by allowing a running start. This allowed the robot to be running at maximum velocity when it entered the distance marked area. The robot traveled at 10.2ftlsec or 6.95mph during this test because it lost no time in slipping while trying to accelerate and stayed on course. 86 Table 6.1 Robot Velocity and Acceleration Data for Grass Field Distance Trial 1 Trial 2 Trial 3 Running (ft) Time Time Time Start Time (sec) (sec) (sec) (set> ...... 0 0 0 0 0 Constant Acceleration 3 0.6 0.5 0.5 0.3 Phase (1-3) 6 0.9 0.9 0.9 0.6 ...... 9 1.3 1.2 1.2 0.9 12 1.5 1.5 1.5 1.1 15 1.8 1.8 2.0 1.4 18 2.1 2.1 2.4 1.7 2 1 2.4 2.4 2.6 2 Constant Velocity 24 2.7 2.7 2.9 2.3 Phase (1-3 2 7 3 .O 3 .O 3.2 2.6 30 3.3 3.3 3.5 2.9 33 3.6 3.6 3.8 3.2 36 3.9 3.9 4.1 3.5 39 4.2 4.3 4.4 3.8 42 4.6 4.5 4.7 4.1 ...... 4 5 4.9 4.7 4.8 4.4
Velocity (ftlsec) 10.0 9.72 10.0 10.2
Acceleration (ft/sec2 14.8 14.8 14.8
Average Velocity (ftlsec) 9.9
Average Acceleration 14.8 (ft/sec2)
On brushed concrete two trials were run; see Table 6.2 for the data. The robot tires did not slip as they did on grass. The distance used was 30 feet with 5 pads each of
6 foot in length. Video was taken and the acceleration was found to be 10.66ft/sec2. This does make sense based on the method (starting time at first sign of movement) used to calculate acceleration and because the wheels are not slipping. It should take longer for 87 the robot to come up to speed because the tires will not be at their maximum speed when motion occurs. The constant velocity found (averaged between the two trials) on the concrete was 10.2ftlsec or 6.95mph. As with the grass trial, velocity was measured from the point at which the time did not change between successive distance points.
Table 6.2 Robot Velocity and Acceleration Data for Brushed Concrete Distance (ft) Trial 1 Time (sec) Trial 2 Time (sec) ...... Constant Acceleration 0 0 0 Phase 6 0.9 0.9 ...... 12 1.5 1.5 Constant Velocity 18 2.2 2.1 Phase 24 2.7 2.7 ...... 30 3.2 3.3
Velocity (ftlsec) 10.4 10
Acceleration (ft/sec2) 10.67 10.67
Average Velocity (ftlsec) 10.2
Average Acceleration 10.67 (ft/sec2)
It should be brought to attention that when the robot was being tested on the grass field it had a full set of batteries while the concrete trial did not. The robot had not been moved under its own power until the time trials on the grass field began. This is important because the motor manufacturer informed me that on a fresh set of batteries the motors can run at 5300rpm at the armature, not the specified 4700rpm. This faster speed gives 265rpm at the gear-head. This can cause greater acceleration due to higher wheel speed when taking off (slipping then gripping) and a higher constant velocity as shown in 88 Equation 6.5. The duration at which the motor will run at 5300rpm was not disclosed by the manufacturer.
265rev 1min ,~(lOin) 1ft 1 1.56ft -*- *-- - -= 7.88mph (6.5) min 60sec rev 12in sec
The gear-head of the motor also serves as a brake. The gear-head can bring the robot to a stop in less than 6ft if the robot is running at full speed. In some cases, the rear set of tires lose contact with the ground due to the sudden stop. Rapidly trying to reverse the direction of travel can cause a problem. If the robot is running forward and, without allowing the robot to come to a stop, is given the command to go backward it will roll over onto its back. This happened while being evaluated in a grass field the result of which can be seen in Figure 6.3.
Figure 6.3 Pushing the Robot onto its Wheels
6.2 Traction on Linoleum, Concrete, and Grass
Overall the traction of the robot is very good. On linoleum it is capable of pulling a 1851b (conservative weight estimate; no sled, wheels etc where used to aid motion) person without slipping or needing full power. On grass, as shown in Figure 6.4, it is 89 also able to do this without the aid of a sled or wheeled cart of some sort, but does need more power (although not maximum power) due to wheel slippage. This has not been tried on concrete.
Figure 6.4 Dragging Jason Norman
While accelerating on grass or linoleum all wheels do slip if attempting to accelerate quickly but when they do catch, acceleration is rapid for the motors do not lose much angular speed because they are capable of handling a much heavier load than the robot presents. Acceleration on brushed concrete is more gradual but much more steady because the wheels do not slip.
6.3 Turning
The turning ability of the robot is good on all surfaces. Differential-steering on all three of the above mentioned surfaces works well. When traveling at high speeds, the differential-steering has a more gradual effect than at lower speeds. This is good because it prevents a sharp turn that could cause a rollover. However, the Roboteq AX2550 sets the power that each motor gets when attempting to differentially steer. Because it does so 90 internally, there is no way to change how this is done or adjust the settings while in radio control mode. When a micro computer is used, the wheel speed will be set by the computer and thus will allow as sharp or as gradual a turn while using differential- steering.
On brushed concrete and linoleum, the differential-steering is very good overall, even at high speeds. However, while attempting to perform high speed differential turns in grass, a problem was found. The stiffness of the frame allowed some tires to lose contact with the ground when a hole or bump was hit. This caused the turns to be much looser and longer because not all tires were driving at the same time. If no obstacles were encountered in the grass field the turns were acceptable, they where not acceptable when obstacles were present.
Skid-steering works equally well on all three of the surfaces previously mentioned. Because the robot is not in forward or backward motion, rather spinning in a circle, none of the problems found with differential-steering occurred while skid-steering.
Cosmetic damage did occur to each surface though. On brushed concrete black tire marks were left after skid-steering. It should also be noted that before the motor mounts were added, the robot had a tendency to hop while skid-steering on brushed concrete.
This is no longer present with the addition of the motor mounts. Linoleum could also have black tire marks left from the robot. The marks have not been as consistently left as the ones found on brushed concrete but they have occurred.
Grass is dug up by the robot. While skid-steering it is not uncommon to see grass flying up from the wheels and ruts being left in the wake of the robot. On wet grass, the 9 1 problem is even worse. This is more than likely due to the weight of the robot and the tire tread pattern.
6.4 Commanded vs. Actual Motion
For the majority of the tests, the commanded motion and the actual motion of the robot coincided very well. When instructed to turn the robot does what it is told and the turns can be varied in sharpness or speed. Acceleration and stopping are easily done and the response time for acceleration can be adjusted in the AX2550. The only problems occur when the terrain is uneven and some robot wheels lose contact with the ground.
This causes unwanted motion or a lack of wanted motion. Drift was also measured while testing velocity. A piece of nylon rope was stretched 45 ft in length and pulled tight to ensure that it remained straight. The robot was then centered over the rope with the front tires at the zero-distance marker. The robot was then driven at a slow speed and stopped when the rear tires were in line with the 45ft-distance marker. The drift was the measurement of distance from the nylon rope to the center of the chassis between the rear tires, as shown below in Figure 6.5. This test was performed twice and each test had the robot drifting to the right of the line at a distance of 30 inches. Figure 6.5 Robot Drifting to Right
6.4 Motion with Encoders vs. Motion without Encoders
At the present time only two of the four encoders on this robot are functional.
The functioning encoder set controls the front of the robot. When using the encoders, it can be seen that they do synchronize the speed of the front tires when attempting to turn by skid-steering or normal operation such as driving forward or backward. The encoders do cause a problem that is not present when encoders are not used. Under normal driving with encoders, the robot pulls to the right. It pulls very sharply and requires a large amount of compensation from the radio control operator to stay driving straight. This happens because the number three motor located in the rear of the left side is not as fast as the other three motors. The cause of this is unknown at this time. The AX2550 uses the motor with the least load as its speed setting while in closed-loop with encoder feedback operated under radio control. Because the front motor on the left side is pulling an additional load from the slower rear motor, it is continually getting more power than 9 3 the motor on the right front. This causes it to be continually driven at a higher speed than the right side causing the right handed turn.
6.5 Frame Stiffness
Before final testing of the robot was done, motor mounts were added to more rigidly connect the frame and motors and to ensure the integrity of the motor gear-head while traversing stairs or rough terrain. Previously, the frame would flex slightly and allow better contact with the ground in mildly uneven terrain. It would also allow the motors to move a little while turning on brushed concrete and carpet, adding to the hop experienced by the robot. With the addition of the motor mounts, the tires are more likely to lose contact with the ground in mildly uneven terrain because the frame does not flex. This can cause problems with robot motion as was evident during testing.
However, on brushed concrete the robot does not hop as much because the motors are now fixed more rigidly to the frame.
6.6 Operational Procedures
The robot in this thesis is easy to operate. There are two modes to be followed when operating the mobile robot. First is radio controller operation and the second is power activation. The only features used on the Futaba 9CAP transmitter are the two throttle sticks. The following will detail the transmitter operation.
1. Push left throttle stick up to turn left.
2. Push left throttle stick down to turn right.
3. Push right throttle up to go forward.
4. Push right throttle down to go backward. 94 Mixing any of these commands will cause robot to skid-steer or differential-steer depending on the position of each throttle stick. Each throttle can move left to right as well as up and down. The left to right motion will cause no movement of the robot, as these channels have been shutdown and are ignored by the Roboteq AX2550.
The second mode of operation is powering on the robot. This is accomplished by turning the proper switches on. It does not matter in what order the switches are activated; this will not cause any damage or movement of the robot. However, the recommended procedure is listed below.
1. Turn on the radio transmitter.
2. Turn on the radio receiver.
3. Flip the Roboteq AX2550 switch located on side of vehicle to opedoff (this is
considered "ON" by the AX2550).
4. Pull up main power switches (2) located in front of robot to activate main power.
The proper method of shutting down the robot is the reversal of the procedure to turn the robot on. The robot will not move until all switches are in there proper position.
Care should be taken to ensure that while activating the robot, each throttle stick on the radio transmitter is at the zero position. If this is not the case, the robot will move as soon as main power is online. 7. Conclusions
This thesis describes mobile robots in industry and academia as well as the
RoboCup Rescue Robot League for search and rescue. A description of the competition held at NIST and the goals of this competition are given. The evolution of the search and rescue mobile robot developed at Ohio University is shown by revealing the research into robots that can be bought from industry or other vehicle types such as the Power-Wheels platform that can be modified into a robot. Components needed for obstacle and victim detection are discussed. The robot developed has the stall-torque model derived and tested. Solid modeling and FEA analysis results are shown to demonstrate the validity of the design and its theoretical limits. The capabilities of the mobile robot were evaluated in the field and found to be acceptable.
In finishing this thesis, it became clear that certain aspects of this project need to be updated to ensure the success of this robot. First and foremost are the encoders. To allow low level closed-loop control by radio control or micro computer the rear encoders must be fixed and replaced. This will mitigate the right turn seen by only using two encoders. Secondly, the aluminum pin-jointed frame should be utilized. This will allow the wheels to maintain contact with the ground in uneven or rough terrain, unlike the stiff steel frame. However, when the motors are mounted to the pin-jointed frame, care must be shown to allow the bigger tires (which have been ordered) to fit properly. The third problem is the tires. The 10 inch tires are too small to allow travel over stairs. The
Stocker stairwell has a lip that effectively cups the wheel and prevents it from climbing over the stair. Another problem with the tires is that they allow the motor mounts facing 96 the center of the chassis to come into contact with obstacles that the robot is trying to climb over. This happened when attempting to climb a curb. The larger tires will prevent this because they are 4 inches larger in diameter and would only need to be 1 inch larger in diameter to prevent the motor mounts from extending past the tire.
The most important aspect needed for this robot is the navigation system integrated with the SICK LMS 200 laser unit. By using all of the AX2550's capabilities, the large power of the robot, and the precision that will be available when the navigation system and laser unit are coupled, this robot will be successful. It is my hope that the robot will be able to operate autonomously from the navigation system currently being developed for the EE 495 senior design project (autonomous lawn mower) which uses the same motor controllers.
The closed-loop control system for this mobile robot will need to do two things to ensure the proper motion of this robot. The first item will be to detect wheels that are slipping and have a method of dealing with this when it occurs. The second item is keeping the robot from flipping over when a sudden direction change or stop is required.
The Roboteq AX2550 has the ability to send motor speed data. This will allow the navigation system to work in conjunction with the control system to find which wheels are slipping, if it is causing unwanted motion, and choose a protocol to deal with the slipping wheel. To keep the robot from overturning when attempting a direction reversal the current delivered to each motor must be monitored. By not allowing the maximum current to be delivered, the motors will not be able to achieve their maximum torque. By limiting torque, the robot will not be capable of turning itself over. 9 7 In order to keep the robot from harming grass or other surfaces a steering mechanism may need to be developed. The EE 495 senior design project uses tires specifically desired to keep from harming grass. Perhaps these tires could be adapted to this mobile robot and tested. One question for the next person who works on this robot will be how to keep the robot form marring surfaces upon which it travels. References
0. Abdulla, A. Ball, A. Crews, J. Fink, J. Fowler, J. Heath, N. Killen, T. Lambert, J. Moore, J. Pressley, J. Pugalee, P. Richards, S. Saurabh, G. Sakshi, G. Stutts, B. Toler, J. Vest, 2001, "Bluefield State College - ENIAC" International Ground Vehicle Competition (IGVC) Design Report 2001 #41.
Active Media Robotics Website, PA-3T, October 2002, http://w\\t~~.a~ti~robots.~o111lROBOTS~p2at.html
W. Agnew, 2002, "Future Drivers; Autonomy, Intelligence in Robot Competition" GPS World: November 2002
Angelus Research Corporation Website, ART 1, October 2002, http:, 13 fir\+ .angel~lsresearcI~.com~art.htni
Applied A1 System Inc Website, GAIA-2, October 2002, I~tt!~:~t~~~t.w.aai.ca/products~r~~b~~ts~aia2.html
R. Arkin, M. Kaess, J. Rossignac, 2002, "Compact Encoding of Robot-Generated 3D Maps for Efficient Wireless Transmission" College of Computing, Georgia Institute of Technology.
Autonomous Solutions Inc Website, W.A.T.V, July 2003, http: I \z u\+.autonomoussolutions.com research/prolects/w:~t\.html
R. Bolsteman, 2002, "NIST Industrial Autonomous Vehicle Project" NIST, Power Point Presentation.
A. Cahill, A. Mordovanaki, J. Najor, A. Sandhu, B. Schaar, H. Young, 2002, "University of Michigan Dearborn - FAST" International Ground Vehicle Competition (IGVC) Design Report 2002 #13.
Center for Robot-Assisted Search and Rescue: CRASAR at USF, April 2003, lltt~:l,crasar.csee.usf.edu,roboticsI'
L. Chen, S. Nair, A. Shvartsman, 2003, "Lawrence Technological University - CotigoBot" International Ground Vehicle Competition (IGVC) Design Report 2003 #56.
E. Esmailzadeh, G.R. Vossoughi, A. Goodarzi, 2001, "Dynamic Modeling and Analysis of a Four Motorized Wheels Electric Vehicle" Vehicle Systems Dynamics, Vol. 35, No.3, pp. 163-194, 2001. 9 9 C. Evans, D. MacArthur, D. Novick, A. Pasha, E. Zawodny, 2002, "University of Florida - UF Eliminator" International Ground Vehicle Competition (IGVC) Design Report 2002 #22.
J.M. Evans, T. Chang, T.H. Hong, R. Bostelman, and W.R. Bunch, 2002, "Three Dimensional Data Capture in Indoor Environments for Autonomous Navigation" NIST Internal Report #69 12.
Fischer-Price, July 2003, http: inuu.fislicr-price.con1;us powcnvhcels
Georgia Tech Mobile Robot Lab, September 2003, llttp:i/~\~\.\..cc..qa tcch.~du/ai/robot-labi'researcl7~3d1
HobbyTron Website, December 2002, wu.w.hobbytron.com
International Ground Vehicle Competition (IGVC) Design Reports Website, November 2002, http:ilww.igvc.orgideplo\;~reports.htn~
iRobot Website, October 2002, http:/!wu u .irobot.com
A. Jacoff, E. Messina, J. Evans, 2001, "Experiences in Deploying Test Arenas for Autonomous Mobile Robots" Proceeding of the 2001 Performance Metrics for Intelligent Systems (PerMIS) Workshop
Kadtronix Website, September 2003, 1ittp:iil~irw~.kadtronix.com/
K. Miller, 2002, "Rugged Mobile Robotic System for Surveillance and Reconnaissance" Sandia National Laboratories. http: ' n~vw.saiidia.rrot~JisrclMar\in.htm1
H. Kitano, S.Tadokoro, 2001, "RoboCup Rescue A Grand Challenge for Multiagent and Intelligent Systems" A1 Magazine Spring 2001, http:li\.tl~\u.findru-ticles.coni!cf dlslrn248311 22'7339342 1/p I/article.ihtlnl
NIST RoboCupRescue 2003 Website, January 2003, littp:ii~~~~v~v,isd.n1el.nist.~ov~RoboCup3003/arc11as.htm-
NIST Test Arena and Performance Website, November 2002, http:~\v~~~v.isd.mcl.nist.go~/proiccts'USAR:
NPC Robotics Website, October 2003, hltp:~ R. Riggins, 2002, "Bluefield State College - Centurion 11" International Ground Vehicle Competition (IGVC) Design Report 2002 #lo. 100 R. Riggins, 2003, "Bluefield State College - Vasilius" International Ground Vehicle Competition (IGVC) Design Report 2003 #53. RoboCup Official RoboCupRescue Website, July 2002, http:iiwm \\2..robocup.orgi'gan1es,3O.htnll Roboteq Website, September 2003, littp://\v\.vw.roboteq.com~ SICK Website, November 2002, http://wwfi .sick.dcldc/products/catc~0ric'~~a~t~~/1a~cr~iicsrn1tsystcnisior1nis200i ndoorlen. htrnl F. Solc, L. Zalud, B. Honzik, 2004, "Mathematical Model of the Skid-Steered Mobile Robot" Dept of Control, Measurement and Instrumentation, Faculty of Electrical Engineering and Computer Science, Brno University of Technology. J. Swartz, 2003, "New Breed of Robots Takes War to Next Level", USA Today: May 12,2003. R. Toogood, 2000, "University of Alberta - Polar Bear" International Ground Vehicle Competition (IGVC) Design Report 2000 #24. R. Toogood, 2001, "University of Alberta - Kodiak" International Ground Vehicle Competition (IGVC) Design Report 2001 #61. Tower Hobbies, July 2003, ww~.towerhobbies.com Walmart, July 2003, u.ww.walr~~art.corn