Leg Design and Stair Climbing Control for the Rhex Robotic Hexapod
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Smithsonian Institution Archives (SIA)
SMITHSONIAN OPPORTUNITIES FOR RESEARCH AND STUDY 2020 Office of Fellowships and Internships Smithsonian Institution Washington, DC The Smithsonian Opportunities for Research and Study Guide Can be Found Online at http://www.smithsonianofi.com/sors-introduction/ Version 2.0 (Updated January 2020) Copyright © 2020 by Smithsonian Institution Table of Contents Table of Contents .................................................................................................................................................................................................. 1 How to Use This Book .......................................................................................................................................................................................... 1 Anacostia Community Museum (ACM) ........................................................................................................................................................ 2 Archives of American Art (AAA) ....................................................................................................................................................................... 4 Asian Pacific American Center (APAC) .......................................................................................................................................................... 6 Center for Folklife and Cultural Heritage (CFCH) ...................................................................................................................................... 7 Cooper-Hewitt, -
Remote and Autonomous Controlled Robotic Car Based on Arduino with Real Time Obstacle Detection and Avoidance
Universal Journal of Engineering Science 7(1): 1-7, 2019 http://www.hrpub.org DOI: 10.13189/ujes.2019.070101 Remote and Autonomous Controlled Robotic Car based on Arduino with Real Time Obstacle Detection and Avoidance Esra Yılmaz, Sibel T. Özyer* Department of Computer Engineering, Çankaya University, Turkey Copyright©2019 by authors, all rights reserved. Authors agree that this article remains permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Abstract In robotic car, real time obstacle detection electronic devices. The environment can be any physical and obstacle avoidance are significant issues. In this study, environment such as military areas, airports, factories, design and implementation of a robotic car have been hospitals, shopping malls, and electronic devices can be presented with regards to hardware, software and smartphones, robots, tablets, smart clocks. These devices communication environments with real time obstacle have a wide range of applications to control, protect, image detection and obstacle avoidance. Arduino platform, and identification in the industrial process. Today, there are android application and Bluetooth technology have been hundreds of types of sensors produced by the development used to implementation of the system. In this paper, robotic of technology such as heat, pressure, obstacle recognizer, car design and application with using sensor programming human detecting. Sensors were used for lighting purposes on a platform has been presented. This robotic device has in the past, but now they are used to make life easier. been developed with the interaction of Android-based Thanks to technology in the field of electronics, incredibly device. -
Kinematic Modeling of a Rhex-Type Robot Using a Neural Network
Kinematic Modeling of a RHex-type Robot Using a Neural Network Mario Harpera, James Paceb, Nikhil Guptab, Camilo Ordonezb, and Emmanuel G. Collins, Jr.b aDepartment of Scientific Computing, Florida State University, Tallahassee, FL, USA bDepartment of Mechanical Engineering, Florida A&M - Florida State University, College of Engineering, Tallahassee, FL, USA ABSTRACT Motion planning for legged machines such as RHex-type robots is far less developed than motion planning for wheeled vehicles. One of the main reasons for this is the lack of kinematic and dynamic models for such platforms. Physics based models are difficult to develop for legged robots due to the difficulty of modeling the robot-terrain interaction and their overall complexity. This paper presents a data driven approach in developing a kinematic model for the X-RHex Lite (XRL) platform. The methodology utilizes a feed-forward neural network to relate gait parameters to vehicle velocities. Keywords: Legged Robots, Kinematic Modeling, Neural Network 1. INTRODUCTION The motion of a legged vehicle is governed by the gait it uses to move. Stable gaits can provide significantly different speeds and types of motion. The goal of this paper is to use a neural network to relate the parameters that define the gait an X-RHex Lite (XRL) robot uses to move to angular, forward and lateral velocities. This is a critical step in developing a motion planner for a legged robot. The approach taken in this paper is very similar to approaches taken to learn forward predictive models for skid-steered robots. For example, this approach was used to learn a forward predictive model for the Crusher UGV (Unmanned Ground Vehicle).1 RHex-type robot may be viewed as a special case of skid-steered vehicle as their rotating C-legs are always pointed in the same direction. -
An Innovative Mechanical and Control Architecture for a Biomimetic Hexapod for Planetary Exploration M
An Innovative Mechanical and Control Architecture for a Biomimetic Hexapod for Planetary Exploration M. Pavone∗, P. Arenax and L. Patane´x ∗Scuola Superiore di Catania, Via S. Paolo 73, 95123 Catania, Italy xDipartimento di Ingegneria Elettrica Elettronica e dei Sistemi, Universita` degli Studi di Catania, Viale A. Doria, 6 - 95125 Catania, Italy Abstract— This paper addresses the design of a six locomotion are: wheels, caterpillar treads and legs. legged robot for planetary exploration. The robot is Wheeled and tracked robots are much easier to design specifically designed for uneven terrains and is bio- and to implement if compared with legged robots and logically inspired on different levels: mechanically as led to successful missions like Mars Pathfinder or well as in control. A novel structure is developed Spirit and Opportunity; nevertheless, they carry a set basing on a (careful) emulation of the cockroach, whose of disadvantages that hamper their use in more com- extraordinary agility and speed are principally due to its self-stabilizing posture and specializing legged plex explorative tasks. Firstly, wheeled and tracked function. Structure design enhances these properties, vehicles, even if designed specifically for harsh ter- in particular with an innovative piston-like scheme rains, cannot maneuver over an obstacle significantly for rear legs, while avoiding an excessive and useless shorter than the vehicle itself; a legged vehicle, on the complexity. Locomotion control is designed following an other hand, could be expected to climb an obstacle analog electronics approach, that in space applications up to twice its own height, much like a cockroach could hold many benefits. In particular, the locomotion can. -
Human to Robot Whole-Body Motion Transfer
Human to Robot Whole-Body Motion Transfer Miguel Arduengo1, Ana Arduengo1, Adria` Colome´1, Joan Lobo-Prat1 and Carme Torras1 Abstract— Transferring human motion to a mobile robotic manipulator and ensuring safe physical human-robot interac- tion are crucial steps towards automating complex manipu- lation tasks in human-shared environments. In this work, we present a novel human to robot whole-body motion transfer framework. We propose a general solution to the correspon- dence problem, namely a mapping between the observed human posture and the robot one. For achieving real-time imitation and effective redundancy resolution, we use the whole-body control paradigm, proposing a specific task hierarchy, and present a differential drive control algorithm for the wheeled robot base. To ensure safe physical human-robot interaction, we propose a novel variable admittance controller that stably adapts the dynamics of the end-effector to switch between stiff and compliant behaviors. We validate our approach through several real-world experiments with the TIAGo robot. Results show effective real-time imitation and dynamic behavior adaptation. Fig. 1. Transferring human motion to robots while ensuring safe human- This constitutes an easy way for a non-expert to transfer a robot physical interaction can be a powerful and intuitive tool for teaching assistive tasks such as helping people with reduced mobility to get dressed. manipulation skill to an assistive robot. The classical approach for human motion transfer is I. INTRODUCTION kinesthetic teaching. The teacher holds the robot along the Service robots may assist people at home in the future. trajectories to be followed to accomplish a specific task, However, robotic systems still face several challenges in while the robot does gravity compensation [6]. -
Annual Report 2014 OUR VISION
AMOS Centre for Autonomous Marine Operations and Systems Annual Report 2014 Annual Report OUR VISION To establish a world-leading research centre for autonomous marine operations and systems: To nourish a lively scientific heart in which fundamental knowledge is created through multidisciplinary theoretical, numerical, and experimental research within the knowledge fields of hydrodynamics, structural mechanics, guidance, navigation, and control. Cutting-edge inter-disciplinary research will provide the necessary bridge to realise high levels of autonomy for ships and ocean structures, unmanned vehicles, and marine operations and to address the challenges associated with greener and safer maritime transport, monitoring and surveillance of the coast and oceans, offshore renewable energy, and oil and gas exploration and production in deep waters and Arctic waters. Editors: Annika Bremvåg and Thor I. Fossen Copyright AMOS, NTNU, 2014 www.ntnu.edu/amos AMOS • Annual Report 2014 Table of Contents Our Vision ........................................................................................................................................................................ 2 Director’s Report: Licence to Create............................................................................................................................. 4 Organization, Collaborators, and Facts and Figures 2014 ......................................................................................... 6 Presentation of New Affiliated Scientists................................................................................................................... -
AUV Adaptive Sampling Methods: a Review
applied sciences Review AUV Adaptive Sampling Methods: A Review Jimin Hwang 1 , Neil Bose 2 and Shuangshuang Fan 3,* 1 Australian Maritime College, University of Tasmania, Launceston 7250, TAS, Australia; [email protected] 2 Department of Ocean and Naval Architectural Engineering, Memorial University of Newfoundland, St. John’s, NL A1C 5S7, Canada; [email protected] 3 School of Marine Sciences, Sun Yat-sen University, Zhuhai 519082, Guangdong, China * Correspondence: [email protected] Received: 16 July 2019; Accepted: 29 July 2019; Published: 2 August 2019 Abstract: Autonomous underwater vehicles (AUVs) are unmanned marine robots that have been used for a broad range of oceanographic missions. They are programmed to perform at various levels of autonomy, including autonomous behaviours and intelligent behaviours. Adaptive sampling is one class of intelligent behaviour that allows the vehicle to autonomously make decisions during a mission in response to environment changes and vehicle state changes. Having a closed-loop control architecture, an AUV can perceive the environment, interpret the data and take follow-up measures. Thus, the mission plan can be modified, sampling criteria can be adjusted, and target features can be traced. This paper presents an overview of existing adaptive sampling techniques. Included are adaptive mission uses and underlying methods for perception, interpretation and reaction to underwater phenomena in AUV operations. The potential for future research in adaptive missions is discussed. Keywords: autonomous underwater vehicle(s); maritime robotics; adaptive sampling; underwater feature tracking; in-situ sensors; sensor fusion 1. Introduction Autonomous underwater vehicles (AUVs) are unmanned marine robots. Owing to their mobility and increased ability to accommodate sensors, they have been used for a broad range of oceanographic missions, such as surveying underwater plumes and other phenomena, collecting bathymetric data and tracking oceanographic dynamic features. -
Towards Pronking with a Hexapod Robot
Towards pronking with a hexapod robot Dave McMordie Department of Electrical Engineering McGill University, Montreal, Canada July, 2002 A thesis submitted to the Faculty of Graduate 5tudies and Research in partial fulfillment of the requirements of the degree Master of Engineering © Dave McMordie, 2002 National Library Bibliothèque nationale 1+1 of Canada du Canada Acquisitions and Acquisisitons et Bibliographie Services services bibliographiques 395 Wellington Street 395, rue Wellington Ottawa ON K1A DN4 Ottawa ON K1A DN4 Canada Canada Your file Votre référence ISBN: 0-612-85890-1 Our file Notre référence ISBN: 0-612-85890-1 The author has granted a non L'auteur a accordé une licence non exclusive licence allowing the exclusive permettant à la National Library of Canada to Bibliothèque nationale du Canada de reproduce, loan, distribute or sell reproduire, prêter, distribuer ou copies of this thesis in microform, vendre des copies de cette thèse sous paper or electronic formats. la forme de microfiche/film, de reproduction sur papier ou sur format électronique. The author retains ownership of the L'auteur conserve la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor substantial extracts from it Ni la thèse ni des extraits substantiels may be printed or otherwise de celle-ci ne doivent être imprimés reproduced without the author's ou aturement reproduits sans son permission. autorisation. Canada Abstract RHex is a robotic hexapod with springy legs and just six actuated degrees of freedom. This work presents the development of a pronking gait for RHex, extending its efficiency and speed by exploiting its springy legs for hopping. -
Development of an Open Humanoid Robot Platform for Research and Autonomous Soccer Playing
Development of an Open Humanoid Robot Platform for Research and Autonomous Soccer Playing Karl J. Muecke and Dennis W. Hong RoMeLa: Robotics and Mechanisms Lab Virginia Tech Blacksburg, VA 24061 [email protected], [email protected] Abstract This paper describes the development of a fully autonomous humanoid robot for locomotion research and as the first US entry in to RoboCup. DARwIn (Dynamic Anthropomorphic Robot with Intelligence) is a humanoid robot capable of bipedal walking and performing human like motions. As the years have progressed, DARwIn has evolved from a concept to a sophisticated robot platform. DARwIn 0 was a feasibility study that investigated the possibility of making a humanoid robot walk. Its successor, DARwIn I, was a design study that investigated how to create a humanoid robot with human proportions, range of motion, and kinematic structure. DARwIn IIa built on the name ªhumanoidº by adding autonomy. DARwIn IIb improved on its predecessor by adding more powerful actuators and modular computing components. Finally, DARwIn III is designed to take the best of all the designs and incorporate the robot's most advanced motion control yet. Introduction Dynamic Anthropomorphic Robot with Intelligence (DARwIn), a humanoid robot, is a sophisticated hardware platform used for studying bipedal gaits that has evolved over time. Five versions of DARwIn have been developed, each an improvement on its predecessor. The first version, DARwIn 0 (Figure 1a), was used as a design study to determine the feasibility of creating a humanoid robot abd for actuator evaluation. The second version, DARwIn I (Figure 1b), used improved gaits and software. -
Autonomous Navigation of Hexapod Robots with Vision-Based Controller Adaptation
Research Collection Conference Paper Autonomous Navigation of Hexapod Robots With Vision-based Controller Adaptation Author(s): Bjelonic, Marko; Homberger, Timon; Kottege, Navinda; Borges, Paulo; Chli, Margarita; Beckerle, Philipp Publication Date: 2017 Permanent Link: https://doi.org/10.3929/ethz-a-010859391 Originally published in: http://doi.org/10.1109/ICRA.2017.7989655 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Autonomous Navigation of Hexapod Robots With Vision-based Controller Adaptation Marko Bjelonic1∗, Timon Homberger2∗, Navinda Kottege3, Paulo Borges3, Margarita Chli4, Philipp Beckerle5 Abstract— This work introduces a novel hybrid control architecture for a hexapod platform (Weaver), making it capable of autonomously navigating in uneven terrain. The main contribution stems from the use of vision-based exte- roceptive terrain perception to adapt the robot’s locomotion parameters. Avoiding computationally expensive path planning for the individual foot tips, the adaptation controller enables the robot to reactively adapt to the surface structure it is moving on. The virtual stiffness, which mainly characterizes the behavior of the legs’ impedance controller is adapted according to visually perceived terrain properties. To further improve locomotion, the frequency and height of the robot’s stride are similarly adapted. Furthermore, novel methods for terrain characterization and a keyframe based visual-inertial odometry algorithm are combined to generate a spatial map of terrain characteristics. Localization via odometry also allows Fig. 1. The hexapod robot Weaver on the multi-terrain testbed. for autonomous missions on variable terrain by incorporating global navigation and terrain adaptation into one control have been used in the literature to perform leg adaptation to architecture. -
Autonomous Mobile Robots Annual Report 1985
The Mobile Robot Laboratory Sonar Mapping, Imaging and Navigation Visual Navigation Road Following i Motion Control The Robots Motivation Publications Autonomous Mobile Robots Annual Report 1985 Mobile Robot Laboratory CM U-KI-TK-86-4 Mobile Robot Laboratory The Robotics Institute Carncgie Mcllon University Pittsburgh, Pcnnsylvania 15213 February 1985 Copyright @ 1986 Carnegie-Mellon University This rcscarch was sponsored by The Office of Naval Research, under Contract Number NO00 14-81-K-0503. 1 Table of Contents The Mobile Robot Laboratory ‘I’owards Autonomous Vchiclcs - Moravcc ct 31. 1 Sonar Mapping, Imaging and Navigation High Resolution Maps from Wide Angle Sonar - Moravec, et al. 19 A Sonar-Based Mapping and Navigation System - Elfes 25 Three-Dirncnsional Imaging with Cheap Sonar - Moravec 31 Visual Navigation Experiments and Thoughts on Visual Navigation - Thorpe et al. 35 Path Relaxation: Path Planning for a Mobile Robot - Thorpe 39 Uncertainty Handling in 3-D Stereo Navigation - Matthies 43 Road Following First Resu!ts in Robot Road Following - Wallace et al. 65 A Modified Hough Transform for Lines - Wallace 73 Progress in Robot Road Following - Wallace et al. 77 Motion Control Pulse-Width Modulation Control of Brushless DC Motors - Muir et al. 85 Kinematic Modelling of Wheeled Mobile Robots - Muir et al. 93 Dynamic Trajectories for Mobile Robots - Shin 111 The Robots The Neptune Mobile Robot - Podnar 123 The Uranus Mobile Robot, a First Look - Podnar 127 Motivation Robots that Rove - Moravec 131 Bibliography 147 ii Abstract Sincc 13s 1. (lic Mobilc I<obot IAoratory of thc Kohotics Institute 01' Crrrncfiic-Mcllon IInivcnity has conduclcd hsic rcscarcli in aTCiiS crucial fur ;iiitonomoiis robots. -
The Autonomous Underwater Vehicle Initiative – Project Mako
Published at: 2004 IEEE Conference on Robotics, Automation, and Mechatronics (IEEE-RAM), Dec. 2004, Singapore, pp. 446-451 (6) The Autonomous Underwater Vehicle Initiative – Project Mako Thomas Bräunl, Adrian Boeing, Louis Gonzales, Andreas Koestler, Minh Nguyen, Joshua Petitt The University of Western Australia EECE – CIIPS – Mobile Robot Lab Crawley, Perth, Western Australia [email protected] Abstract—We present the design of an autonomous underwater vehicle and a simulation system for AUVs as part II. AUV COMPETITION of the initiative for establishing a new international The AUV Competition will comprise two different competition for autonomous underwater vehicles, both streams with similar tasks physical and simulated. This paper describes the competition outline with sample tasks, as well as the construction of the • Physical AUV competition and AUV and the simulation platform. 1 • Simulated AUV competition Competitors have to solve the same tasks in both Keywords—autonomous underwater vehicles; simulation; streams. While teams in the physical AUV competition competition; robotics have to build their own AUV (see Chapter 3 for a description of a possible entry), the simulated AUV I. INTRODUCTION competition only requires the design of application Mobile robot research has been greatly influenced by software that runs with the SubSim AUV simulation robot competitions for over 25 years [2]. Following the system (see Chapter 4). MicroMouse Contest and numerous other robot The competition tasks anticipated for the first AUV competitions, the last decade has been dominated by robot competition (physical and simulation) to be held around soccer through the FIRA [6] and RoboCup [5] July 2005 in Perth, Western Australia, are described organizations.