Design and Control of a Large Modular Robot 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, -
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. -
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................................................................................................................... -
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. -
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. -
Design and Realization of a Humanoid Robot for Fast and Autonomous Bipedal Locomotion
TECHNISCHE UNIVERSITÄT MÜNCHEN Lehrstuhl für Angewandte Mechanik Design and Realization of a Humanoid Robot for Fast and Autonomous Bipedal Locomotion Entwurf und Realisierung eines Humanoiden Roboters für Schnelles und Autonomes Laufen Dipl.-Ing. Univ. Sebastian Lohmeier Vollständiger Abdruck der von der Fakultät für Maschinenwesen der Technischen Universität München zur Erlangung des akademischen Grades eines Doktor-Ingenieurs (Dr.-Ing.) genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr.-Ing. Udo Lindemann Prüfer der Dissertation: 1. Univ.-Prof. Dr.-Ing. habil. Heinz Ulbrich 2. Univ.-Prof. Dr.-Ing. Horst Baier Die Dissertation wurde am 2. Juni 2010 bei der Technischen Universität München eingereicht und durch die Fakultät für Maschinenwesen am 21. Oktober 2010 angenommen. Colophon The original source for this thesis was edited in GNU Emacs and aucTEX, typeset using pdfLATEX in an automated process using GNU make, and output as PDF. The document was compiled with the LATEX 2" class AMdiss (based on the KOMA-Script class scrreprt). AMdiss is part of the AMclasses bundle that was developed by the author for writing term papers, Diploma theses and dissertations at the Institute of Applied Mechanics, Technische Universität München. Photographs and CAD screenshots were processed and enhanced with THE GIMP. Most vector graphics were drawn with CorelDraw X3, exported as Encapsulated PostScript, and edited with psfrag to obtain high-quality labeling. Some smaller and text-heavy graphics (flowcharts, etc.), as well as diagrams were created using PSTricks. The plot raw data were preprocessed with Matlab. In order to use the PostScript- based LATEX packages with pdfLATEX, a toolchain based on pst-pdf and Ghostscript was used. -
Robotics Laboratory List
Robotics List (ロボット技術関連コースのある大学) Robotics List by University Degree sought English Undergraduate / Graduate Admissions Office No. University Department Professional Keywords Application Deadline Degree in Lab links Schools / Institutes or others Website Bachelor Master’s Doctoral English Admissions Master's English Graduate School of Science and Department of Mechanical http://www.se.chiba- Robotics, Dexterous Doctoral:June and December ○ http://www.em.eng.chiba- 1 Chiba University ○ ○ ○ Engineering Engineering u.jp/en/ Manipulation, Visual Recognition Master's:June (Doctoral only) u.jp/~namiki/index-e.html Laboratory Innovative Therapeutic Engineering directed by Prof. Graduate School of Science and Department of Medical http://www.tms.chiba- Doctoral:June and December ○ 1 Chiba University ○ ○ Surgical Robotics ○ Ryoichi Nakamura Engineering Engineering u.jp/english/index.html Master's:June (Doctoral only) http://www.cfme.chiba- u.jp/~nakamura/ Micro Electro Mechanical Systems, Micro Sensors, Micro Micro System Laboratory (Dohi http://global.chuo- Graduate School of Science and Coil, Magnetic Resonance ○ ○ Lab.) 2 Chuo University Precision Mechanics u.ac.jp/english/admissio ○ ○ October Engineering Imaging, Blood Pressure (Doctoral only) (Doctoral only) http://www.msl.mech.chuo-u.ac.jp/ ns/ Measurement, Arterial Tonometry (Japanese only) Method Assistive Robotics, Human-Robot Communication, Human-Robot Human-Systems Laboratory http://global.chuo- Graduate School of Science and Collaboration, Ambient ○ http://www.mech.chuo- 2 Chuo University -
Performance Analysis and Terrain Classification for a Legged Robot
Performance analysis and terrain classification for a legged robot over rough terrain Fernando L. Garcia Bermudez, Ryan C. Julian, Duncan W. Haldane, Pieter Abbeel, and Ronald S. Fearing Abstract— Minimally actuated millirobotic crawlers navigate unreliably over uneven terrain–even when designed with in- herent stability–mostly because of manufacturing variabilities and a lack of good models for ground interaction. In this paper, we investigate the performance of a legged robot as it traverses three distinct rough terrains: tile, carpet, and gravel. Furthermore, we present an accurate, robust, low-lag, and efficient algorithm for terrain classification that uses vibration data from the on-board inertial measurement unit and motor control data from back-EMF sensing and magnetic encoders. I. INTRODUCTION Millirobotic crawling platforms have in general been op- timized from a design perspective at the mechanical level. The optimization goal was to achieve a certain behavior optimally, such as sprinting [4][17], climbing [3], walking [18][21], or turning [28]. What was not often reported, Fig. 1: Robotic platform, outfitted with motion capture though, is that although the design may be optimal for a tracking dots, positioned on top of the gravel used for specific task, manufacturing variability can result in poor experimentation. performance. This is even more significant at the millirobot scale and was a particularly crucial limitation of the actuation mechanism of the Micromechanical Flying Insect [1]. rough terrains. Using telemetry gathered from the on-board This has prompted several groups to work on adapting sensors, we then focus on terrain classification. the robot’s gait to achieve better performance at tasks the Previous authors have focused on vibrational terrain clas- robot was not designed for (e.g. -
Principles of Robot Locomotion
Principles of robot locomotion Sven Böttcher Seminar ‘Human robot interaction’ Index of contents 1. Introduction................................................................................................................................................1 2. Legged Locomotion...................................................................................................................................2 2.1 Stability................................................................................................................................................3 2.2 Leg configuration.................................................................................................................................4 2.3 One leg.................................................................................................................................................5 2.4 Two legs...............................................................................................................................................7 2.5 Four legs ..............................................................................................................................................9 2.6 Six legs...............................................................................................................................................11 3 Wheeled Locomotion................................................................................................................................13 3.1 Wheel types .......................................................................................................................................13 -
Dynamically Diverse Legged Locomotion for Rough Terrain
Dynamically diverse legged locomotion for rough terrain The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Byl, Katie, and Russ Tedrake. “Dynamically Diverse Legged Locomotion for Rough Terrain.” Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe International Conference Center, Kobe, Japan, May 12-17, 2009 1607-1608. © Copyright 2009 IEEE. As Published http://dx.doi.org/10.1109/ROBOT.2009.5152757 Publisher Institute of Electrical and Electronics Engineers Version Final published version Citable link http://hdl.handle.net/1721.1/64752 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. 2009 IEEE International Conference on Robotics and Automation Kobe International Conference Center Kobe, Japan, May 12-17, 2009 Dynamically Diverse Legged Locomotion for Rough Terrain Katie Byl and Russ Tedrake Abstract— In this video, we demonstrate the effectiveness of which aim toward precise foot placement often traverse a kinodynamic planning strategy that allows a high-impedance terrain by using relatively slow, deliberate gaits [3], [4], [10], quadruped to operate across a variety of rough terrain. At one [8], [6]. In this video we demonstrate a control approach extreme, the robot can achieve precise foothold selection on intermittent terrain. More surprisingly, the same inherently- which can achieve both precise foot placement, as illustrated stiff robot can also execute highly dynamic and underactuated in Figure 1, and highly dynamic and fast motions, such as motions with high repeatability. -
New Method for Robotic Systems Architecture
NEW METHOD FOR ROBOTIC SYSTEMS ARCHITECTURE ANALYSIS, MODELING, AND DESIGN By LU LI Submitted in partial fulfillment of the requirements For the degree of Master of Science Thesis Advisor: Dr. Roger Quinn Department of Mechanical and Aerospace Engineering CASE WESTERN RESERVE UNIVERSITY August 2019 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of Lu Li candidate for the degree of Master of Science. Committee Chair Dr. Roger Quinn Committee Member Dr. Musa Audu Committee Member Dr. Richard Bachmann Date of Defense July 5, 2019 *We also certify that written approval has been obtained for any proprietary material contained therein. ii Table of Contents Table of Contents ................................................................................................................................................ i List of Tables ....................................................................................................................................................... ii List of Figures .................................................................................................................................................... iii Copyright page .................................................................................................................................................. iv Preface ..................................................................................................................................................................... v Acknowledgements