Omnidirectional Walking and Active Balance for Soccer Humanoid Robot
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Humanoid Teensize Open Platform Nimbro-OP
Proceedings of 17th RoboCup International Symposium, Eindhoven, Netherlands, 2013 Humanoid TeenSize Open Platform NimbRo-OP Max Schwarz, Julio Pastrana, Philipp Allgeuer, Michael Schreiber, Sebastian Schueller, Marcell Missura and Sven Behnke Autonomous Intelligent Systems, Computer Science, Univ. of Bonn, Germany fschwarzm, schuell1, [email protected] fpastrana, allgeuer, schreiber, [email protected] http://ais.uni-bonn.de/nimbro/OP Abstract. In recent years, the introduction of affordable platforms in the KidSize class of the Humanoid League has had a positive impact on the performance of soccer robots. The lack of readily available larger robots, however, severely affects the number of participants in Teen- and AdultSize and consequently the progress of research that focuses on the challenges arising with robots of larger weight and size. This paper presents the first hardware release of a low cost Humanoid TeenSize open platform for research, the first software release, and the current state of ROS-based software development. The NimbRo-OP robot was designed to be easily manufactured, assembled, repaired, and modified. It is equipped with a wide-angle camera, ample computing power, and enough torque to enable full-body motions, such as dynamic bipedal locomotion, kicking, and getting up. 1 Introduction Low-cost and easy to maintain standardized hardware platforms, such as the DARwIn-OP [1], have had a positive impact on the performance of teams in the KidSize class of the RoboCup Humanoid League. They lower the barrier for new teams to enter the league and make maintaining a soccer team with the required number of players easier. Out-of-the-box capabilities like walking and kicking allow the research groups to focus on higher-level perceptual or behavioral skills, which increases the quality of the games and, hence, the attractiveness of RoboCup for visitors and media. -
Malachy Eaton Evolutionary Humanoid Robotics Springerbriefs in Intelligent Systems
SPRINGER BRIEFS IN INTELLIGENT SYSTEMS ARTIFICIAL INTELLIGENCE, MULTIAGENT SYSTEMS, AND COGNITIVE ROBOTICS Malachy Eaton Evolutionary Humanoid Robotics SpringerBriefs in Intelligent Systems Artificial Intelligence, Multiagent Systems, and Cognitive Robotics Series editors Gerhard Weiss, Maastricht, The Netherlands Karl Tuyls, Liverpool, UK More information about this series at http://www.springer.com/series/11845 Malachy Eaton Evolutionary Humanoid Robotics 123 Malachy Eaton Department of Computer Science and Information Systems University of Limerick Limerick Ireland ISSN 2196-548X ISSN 2196-5498 (electronic) SpringerBriefs in Intelligent Systems ISBN 978-3-662-44598-3 ISBN 978-3-662-44599-0 (eBook) DOI 10.1007/978-3-662-44599-0 Library of Congress Control Number: 2014959413 Springer Heidelberg New York Dordrecht London © The Author(s) 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. -
Robot Deep Reinforcement Learning: Tensor State-Action Spaces and Auxiliary Task Learning with Multiple State Representations
Robot Deep Reinforcement Learning: Tensor State-Action Spaces and Auxiliary Task Learning with Multiple State Representations Devin Schwab CMU-RI-TR-20-46 Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Robotics The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 August 19, 2020 Thesis Committee: Manuela Veloso, Chair Katerina Fragkiadaki David Held Martin Riedmiller, Google DeepMind Copyright © 2020 Devin Schwab Keywords: robotics, reinforcement learning, auxiliary task, multi-task learning, transfer learning, deep learning To my friends and family. Abstract A long standing goal of robotics research is to create algorithms that can au- tomatically learn complex control strategies from scratch. Part of the challenge of applying such algorithms to robots is the choice of representation. Reinforcement Learning (RL) algorithms have been successfully applied to many different robotic tasks such as the Ball-in-a-Cup task with a robot arm and various RoboCup robot soccer inspired domains. However, RL algorithms still suffer from issues of large training time and large amounts of required training data. Choosing appropriate rep- resentations for the state space, action space and policy can go a long way towards reducing the required training time and required training data. This thesis focuses on robot deep reinforcement learning. Specifically, how choices of representation for state spaces, action spaces, and policies can reduce training time and sample complexity for robot learning tasks. In particular the focus is on two main areas: 1. Transferrable Representations via Tensor State-Action Spaces 2. Auxiliary Task Learning with Multiple State Representations The first area explores methods for improving transfer of robot policies across environment changes. -
Action Selection in Cooperative Robot Soccer Using Case-Based Reasoning
Action Selection in Cooperative Robot Soccer using Case-Based Reasoning Tesi Doctoral Autora Raquel Ros Espinoza Director Ramon L´opez de M`antaras Tutor Josep Puyol Gruart Programa de Doctorat en Inform`atica Departament de Ci`encies de la Computaci´o Universitat Aut`onoma de Barcelona Realitzada a Institut d’Investigaci´oen Intel.lig`encia Artificial Consejo Superior de Investigaciones Cient´ıficas Bellaterra, Febrer del 2008. al Pepe y a la Mazo iv Acknowledgments Como se suele hacer en estos casos, tendr´ıa que comenzar agradeciendo a mi director de tesis, a Ramon. Y de hecho, lo har´e. Pero no solo por haberme guiado y dado consejo en mi investigaci´on durante estos ´ultimos cuatro a˜nos, sino tambi´en por consentirme y permitirme el cambio de tema tesis el d´ıa que se lo propuse, lo cual adem´as supon´ıa la adquisici´on de nuevos robots. Todo hay que decirlo, y para suerte m´ıa, a ´el tambi´en le hac´ıan gracia estos juguetes, y no fue dif´ıcil convencerlo de este cambio, que finalmente se presenta hoy en esta tesis. Junto a ´el, y aunque a efectos burocr´aticos no figura formalmente, Josep Llu´ıs ha sido mi segundo director. Sin duda alguna las discusiones y reuniones con ´el han sido de gran utilidad a la hora de desarrollar esta tesis, y es por ello que parte de este trabajo se lo debo a ´el. Continuar´eagradeciendo el apoyo de otro “jefe”, aunque un poco m´as lejano a la tesis, que me abri´olas puertas del instituto cuando yo empezaba a descubrir el ´area de la inteligencia artificial. -
Download Complete Issue
International Journal of Robotics and Automation (IJRA) Volume 1, Issue 2, 2010 Edited By Computer Science Journals www.cscjournals.org International Journal of Robotics and Automation (IJRA) Book: 2010 Volume 1, Issue 2 Publishing Date: 31-07-2010 Proceedings ISSN (Online): 2180-1312 This work is subjected to copyright. All rights are reserved whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illusions, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication of parts thereof is permitted only under the provision of the copyright law 1965, in its current version, and permission of use must always be obtained from CSC Publishers. Violations are liable to prosecution under the copyright law. IJE Journal is a part of CSC Publishers http://www.cscjournals.org ©IJE Journal Published in Malaysia Typesetting: Camera-ready by author, data conversation by CSC Publishing Services – CSC Journals, Malaysia CSC Publishers Editorial Preface Robots are becoming part of people's everyday social lives - and will increasingly become so. In future years, robots may become caretaking assistants for the elderly or academic tutors for our children, or medical assistants, day care assistants, or psychological counselors. Robots may become our co-workers in factories and offices, or maids in our homes. It is the second issue of volume first of International Journal of Robotics and Automation (IJRA). IJRA published six times in a year and it is being peer reviewed to very high International standards. IJRA looks to the different aspects like sensors in robot, control systems, manipulators, power supplies and software.