Review on Unmanned Underwater Robotics, Structure Designs, Materials, Sensors, Actuators, and Navigation Control
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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. -
An Overview of Novel Actuators for Soft Robotics
actuators Review An Overview of Novel Actuators for Soft Robotics Pinar Boyraz 1,2,* ID , Gundula Runge 3 and Annika Raatz 3 1 Mechanics and Maritime Sciences Department, Chalmers University of Technology, 41296 Gothenburg, Sweden 2 Mechanical Engineering Department, Istanbul Technical University, Istanbul 34437, Turkey 3 Institut fur Montagetechnik (match), Leibniz Universität Hannover, 30823 Garbsen, Hannover, Germany; [email protected] (G.R.); [email protected] (A.R.) * Correspondence: [email protected]; Tel.: +46-730-49-8780 Received: 10 June 2018; Accepted: 9 August 2018; Published: 16 August 2018 Abstract: In this systematic survey, an overview of non-conventional actuators particularly used in soft-robotics is presented. The review is performed by using well-defined performance criteria with a direction to identify the exemplary and potential applications. In addition to this, initial guidelines to compare the performance and applicability of these novel actuators are provided. The meta-analysis is restricted to five main types of actuators: shape memory alloys (SMAs), fluidic elastomer actuators (FEAs), shape morphing polymers (SMPs), dielectric electro-activated polymers (DEAPs), and magnetic/electro-magnetic actuators (E/MAs). In exploring and comparing the capabilities of these actuators, the focus was on eight different aspects: compliance, topology-geometry, scalability-complexity, energy efficiency, operation range, modality, controllability, and technological readiness level (TRL). The overview presented here provides a state-of-the-art summary of the advancements and can help researchers to select the most convenient soft actuators using the comprehensive comparison of the suggested quantitative and qualitative criteria. Keywords: soft-robotics; actuator performance; SMA; SMP; FEA; DEAP; E/MA 1. -
AI, Robots, and Swarms: Issues, Questions, and Recommended Studies
AI, Robots, and Swarms Issues, Questions, and Recommended Studies Andrew Ilachinski January 2017 Approved for Public Release; Distribution Unlimited. This document contains the best opinion of CNA at the time of issue. It does not necessarily represent the opinion of the sponsor. Distribution Approved for Public Release; Distribution Unlimited. Specific authority: N00014-11-D-0323. Copies of this document can be obtained through the Defense Technical Information Center at www.dtic.mil or contact CNA Document Control and Distribution Section at 703-824-2123. Photography Credits: http://www.darpa.mil/DDM_Gallery/Small_Gremlins_Web.jpg; http://4810-presscdn-0-38.pagely.netdna-cdn.com/wp-content/uploads/2015/01/ Robotics.jpg; http://i.kinja-img.com/gawker-edia/image/upload/18kxb5jw3e01ujpg.jpg Approved by: January 2017 Dr. David A. Broyles Special Activities and Innovation Operations Evaluation Group Copyright © 2017 CNA Abstract The military is on the cusp of a major technological revolution, in which warfare is conducted by unmanned and increasingly autonomous weapon systems. However, unlike the last “sea change,” during the Cold War, when advanced technologies were developed primarily by the Department of Defense (DoD), the key technology enablers today are being developed mostly in the commercial world. This study looks at the state-of-the-art of AI, machine-learning, and robot technologies, and their potential future military implications for autonomous (and semi-autonomous) weapon systems. While no one can predict how AI will evolve or predict its impact on the development of military autonomous systems, it is possible to anticipate many of the conceptual, technical, and operational challenges that DoD will face as it increasingly turns to AI-based technologies. -
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. -
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. -
Customizing a Self-Healing Soft Pump for Robot
ARTICLE https://doi.org/10.1038/s41467-021-22391-x OPEN Customizing a self-healing soft pump for robot ✉ Wei Tang 1, Chao Zhang 1 , Yiding Zhong1, Pingan Zhu1,YuHu1, Zhongdong Jiao 1, Xiaofeng Wei1, ✉ Gang Lu1, Jinrong Wang 1, Yuwen Liang1, Yangqiao Lin 1, Wei Wang1, Huayong Yang1 & Jun Zou 1 Recent advances in soft materials enable robots to possess safer human-machine interaction ways and adaptive motions, yet there remain substantial challenges to develop universal driving power sources that can achieve performance trade-offs between actuation, speed, portability, and reliability in untethered applications. Here, we introduce a class of fully soft 1234567890():,; electronic pumps that utilize electrical energy to pump liquid through electrons and ions migration mechanism. Soft pumps combine good portability with excellent actuation per- formances. We develop special functional liquids that merge unique properties of electrically actuation and self-healing function, providing a direction for self-healing fluid power systems. Appearances and pumpabilities of soft pumps could be customized to meet personalized needs of diverse robots. Combined with a homemade miniature high-voltage power con- verter, two different soft pumps are implanted into robotic fish and vehicle to achieve their untethered motions, illustrating broad potential of soft pumps as universal power sources in untethered soft robotics. ✉ 1 State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, China. email: [email protected]; [email protected] NATURE COMMUNICATIONS | (2021) 12:2247 | https://doi.org/10.1038/s41467-021-22391-x | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-22391-x nspired by biological systems, scientists and engineers are a robotic vehicle to achieve untethered and versatile motions Iincreasingly interested in developing soft robots1–4 capable of when the customized soft pumps are implanted into them. -
Position Control for Soft Actuators, Next Steps Toward Inherently Safe Interaction
electronics Article Position Control for Soft Actuators, Next Steps toward Inherently Safe Interaction Dongshuo Li, Vaishnavi Dornadula, Kengyu Lin and Michael Wehner * Department of Electrical and Computer Engineering, University of California, Santa Cruz, CA 95064, USA; [email protected] (D.L.); [email protected] (V.D.); [email protected] (K.L.) * Correspondence: [email protected] Abstract: Soft robots present an avenue toward unprecedented societal acceptance, utility in popu- lated environments, and direct interaction with humans. However, the compliance that makes them attractive also makes soft robots difficult to control. We present two low-cost approaches to control the motion of soft actuators in applications common in human-interaction tasks. First, we present a passive impedance approach, which employs restriction to pneumatic channels to regulate the inflation/deflation rate of a pneumatic actuator and eliminate the overshoot/oscillation seen in many underdamped silicone-based soft actuators. Second, we present a visual servoing feedback control approach. We present an elastomeric pneumatic finger as an example system on which both methods are evaluated and compared to an uncontrolled underdamped actuator. We perturb the actuator and demonstrate its ability to increase distal curvature around the obstacle and maintain the desired end position. In this approach, we use the continuum deformation characteristic of soft actuators as an advantage for control rather than a problem to be minimized. With their low cost and complexity, these techniques present great opportunity for soft robots to improve human–robot interaction. Citation: Li, D.; Dornadula, V.; Lin, Keywords: soft robot; human–robot interaction; control K.; Wehner, M. Position Control for Soft Actuators, Next Steps toward Inherently Safe Interaction. -
Lab Notebook – Soft Robotics
Technology Lab: Lab Notebook – Soft Robotics ã2018 Boy Scouts of America. All rights reserved. No portion of this publication may be reproduced, stored in a retrieval system, or transmitted in any form by any means without the proper written permission of the Boy Scouts of America or as expressly permitted by law. The design of a circle divided into four quadrants with wavy lines along the perimeter (the “BSA STEM logo”) is a trademark of the Boy Scouts of America. Lab Notebook Soft Robotics OVERVIEW ........................................................................................................................... 3 MEETING 1: SOFT ROBOT STRUCTURES ............................................................................. 5 MEETING 2: POWERING SOFT ROBOTS ............................................................................. 16 MEETING 3: BUILD A SOFT ROBOTIC GRASPER ............................................................... 24 MEETING 4: BUILD A SOFT TENTACLE-ARM ROBOT – PART 1 ......................................... 30 MEETING 5: BUILD A SOFT TENTACLE-ARM ROBOT – PART 2 ........................................ 36 MEETING 6: PROGRAMMING MOTIONS ............................................................................41 2 Lab Notebook Soft Robotics Overview This module will delve into an exciting and newly developing branch of robotics—soft or flexible robotic structures. When you look at an elephant’s trunk or an octopus’s arm, you can see natural examples of flexible structures used to grasp and manipulate objects. There are many tasks in our world that a rigid structure just does not perform well. Soft Robotics explores the development of flexible structures to work in these areas. In this module, you and your team will explore the concept of soft robots and learn how flexible structures move and how they can be programmed to perform useful tasks. This module was developed by the REACH Lab at the University of Tennessee, Knoxville. The group focuses on medical applications of robots and soft robots, and the mathematics behind them. -
Architectures of Soft Robotic Locomotion Enabled by Simple
Architectures of Soft Robotic Locomotion Enabled by Simple Mechanical Principles Liangliang Zhu a, c, Yunteng Cao a, Yilun Liu b, Zhe Yang a, Xi Chen c* a International Center for Applied Mechanics, State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi’an Jiaotong University, Xi’an 710049, China b State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi’an Jiaotong University, Xi’an 710049, China c Columbia Nanomechanics Research Center, Department of Earth and Environmental Engineering, Columbia University, New York, NY 10027, USA Abstract In nature, a variety of limbless locomotion patterns flourish from the small or basic life form (Escherichia coli, the amoeba, etc.) to the large or intelligent creatures (e.g., slugs, starfishes, earthworms, octopuses, jellyfishes, and snakes). Many bioinspired soft robots based on locomotion have been developed in the past decades. In this work, based on the kinematics and dynamics of two representative locomotion modes (i.e., worm-like crawling and snake-like slithering), we propose a broad set of innovative designs for soft mobile robots through simple mechanical principles. Inspired by and go beyond existing biological systems, these designs include 1-D (dimensional), 2-D, and 3-D robotic locomotion patterns enabled by simple actuation of continuous beams. We report herein over 20 locomotion modes achieving various locomotion * Corresponding author at: Columbia Nanomechanics Research Center, Department of Earth and Environmental Engineering, Columbia University, New York, NY10027, USA. Tel.: +1 2128543787. E-mail address: [email protected] (X. Chen). 1 functions, including crawling, rising, running, creeping, squirming, slithering, swimming, jumping, turning, turning over, helix rolling, wheeling, etc. -
Learning Preference Models for Autonomous Mobile Robots in Complex Domains
Learning Preference Models for Autonomous Mobile Robots in Complex Domains David Silver CMU-RI-TR-10-41 December 2010 Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania, 15213 Thesis Committee: Tony Stentz, chair Drew Bagnell David Wettergreen Larry Matthies Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Robotics Copyright c 2010. All rights reserved. Abstract Achieving robust and reliable autonomous operation even in complex unstruc- tured environments is a central goal of field robotics. As the environments and scenarios to which robots are applied have continued to grow in complexity, so has the challenge of properly defining preferences and tradeoffs between various actions and the terrains they result in traversing. These definitions and parame- ters encode the desired behavior of the robot; therefore their correctness is of the utmost importance. Current manual approaches to creating and adjusting these preference models and cost functions have proven to be incredibly tedious and time-consuming, while typically not producing optimal results except in the sim- plest of circumstances. This thesis presents the development and application of machine learning tech- niques that automate the construction and tuning of preference models within com- plex mobile robotic systems. Utilizing the framework of inverse optimal control, expert examples of robot behavior can be used to construct models that generalize demonstrated preferences and reproduce similar behavior. Novel learning from demonstration approaches are developed that offer the possibility of significantly reducing the amount of human interaction necessary to tune a system, while also improving its final performance. Techniques to account for the inevitability of noisy and imperfect demonstration are presented, along with additional methods for improving the efficiency of expert demonstration and feedback. -
Uncorrected Proof
JrnlID 10846_ ArtID 9025_Proof# 1 - 14/10/2005 Journal of Intelligent and Robotic Systems (2005) # Springer 2005 DOI: 10.1007/s10846-005-9025-1 Temporal Range Registration for Unmanned 1 j Ground and Aerial Vehicles 2 R. MADHAVAN*, T. HONG and E. MESSINA 3 Intelligent Systems Division, National Institute of Standards and Technology, Gaithersburg, MD 4 20899-8230, USA; e-mail: [email protected], {tsai.hong, elena.messina}@nist.gov 5 (Received: 24 March 2004; in final form: 2 September 2005) 6 Abstract. An iterative temporal registration algorithm is presented in this article for registering 8 3D range images obtained from unmanned ground and aerial vehicles traversing unstructured 9 environments. We are primarily motivated by the development of 3D registration algorithms to 10 overcome both the unavailability and unreliability of Global Positioning System (GPS) within 11 required accuracy bounds for Unmanned Ground Vehicle (UGV) navigation. After suitable 12 modifications to the well-known Iterative Closest Point (ICP) algorithm, the modified algorithm is 13 shown to be robust to outliers and false matches during the registration of successive range images 14 obtained from a scanning LADAR rangefinder on the UGV. Towards registering LADAR images 15 from the UGV with those from an Unmanned Aerial Vehicle (UAV) that flies over the terrain 16 being traversed, we then propose a hybrid registration approach. In this approach to air to ground 17 registration to estimate and update the position of the UGV, we register range data from two 18 LADARs by combining a feature-based method with the aforementioned modified ICP algorithm. 19 Registration of range data guarantees an estimate of the vehicle’s position even when only one of 20 the vehicles has GPS information. -
The SLS-Generated Soft Robotic Hand – an Integrated Approach Using Additive Manufacturing and Reinforcement Learning
The SLS-generated Soft Robotic Hand – An Integrated Approach using Additive Manufacturing and Reinforcement Learning Arne Rost Corporate Research Festo AG & Co. KG 73734 Esslingen, Germany [email protected] Stephan Schädle Institute for Artificial Intelligence University of Applied Sciences Ravensburg-Weingarten 88250 Weingarten, Germany [email protected] / [email protected] Abstract – To develop a robotic system for a complex task is a time- targeted task execution is trained via Reinforcement Learning, a consuming process. Merging methods available today, a new ap- machine learning approach. Optimization points are subsequently proach for a faster realization of a multi-finger soft robotic hand is derived and fed back into the hardware development. With this presented here. This paper introduces a robotic hand with four Concurrent Engineering strategy a fast development of this robotic fingers and 12 Degrees of Freedom (DoFs) using bellow actuators. hand is possible. The paper outlines the relevant key strategies and The hand is generated via Selective Laser Sintering (SLS), an Additive gives insight into the design process. At the end, the final hand with Manufacturing method. The complex task execution of a specific its capabilities is presented and discussed. action, i.e. the lifting, rotating and precise positioning of a handling- object with this robotic hand, is used to structure the whole develop- Soft Robotic Hand; Reinforcement Learning; Additive Manufacturing; ment process. To validate reliable functionality of the hand from SLS; Concurrent Engineering; Compliant; LearningGripper; the beginning, each development stage is SLS-generated and the I INTRODUCTION Soft robots are one kind of intrinsically safe service robots, which strategies [5, 6].