Learning Flexible and Reusable Locomotion Primitives for a Microrobot Brian Yang, Grant Wang, Roberto Calandra, Daniel Contreras, Sergey Levine, and Kristofer Pister
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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. -
Design and Evaluation of Modular Robots for Maintenance in Large Scientific Facilities
UNIVERSIDAD POLITÉCNICA DE MADRID ESCUELA TÉCNICA SUPERIOR DE INGENIEROS INDUSTRIALES DESIGN AND EVALUATION OF MODULAR ROBOTS FOR MAINTENANCE IN LARGE SCIENTIFIC FACILITIES PRITHVI SEKHAR PAGALA, MSC 2014 DEPARTAMENTO DE AUTOMÁTICA, INGENIERÍA ELECTRÓNICA E INFORMÁTICA INDUSTRIAL ESCUELA TÉCNICA SUPERIOR DE INGENIEROS INDUSTRIALES DESIGN AND EVALUATION OF MODULAR ROBOTS FOR MAINTENANCE IN LARGE SCIENTIFIC FACILITIES PhD Thesis Author: Prithvi Sekhar Pagala, MSC Advisors: Manuel Ferre Perez, PhD Manuel Armada, PhD 2014 DESIGN AND EVALUATION OF MODULAR ROBOTS FOR MAINTENANCE IN LARGE SCIENTIFIC FACILITIES Author: Prithvi Sekhar Pagala, MSC Tribunal: Presidente: Dr. Fernando Matía Espada Secretario: Dr. Claudio Rossi Vocal A: Dr. Antonio Giménez Fernández Vocal B: Dr. Juan Antonio Escalera Piña Vocal C: Dr. Concepción Alicia Monje Micharet Suplente A: Dr. Mohamed Abderrahim Fichouche Suplente B: Dr. José Maráa Azorín Proveda Acuerdan otorgar la calificación de: Madrid, de de 2014 Acknowledgements The duration of the thesis development lead to inspiring conversations, exchange of ideas and expanding knowledge with amazing individuals. I would like to thank my advisers Manuel Ferre and Manuel Armada for their constant men- torship, support and motivation to pursue different research ideas and collaborations during the course of entire thesis. The team at the lab has not only enriched my professionally life but also in Spanish ways. Thank you all the members of the ROMIN, Francisco, Alex, Jose, Jordi, Ignacio, Javi, Chema, Luis .... This research project has been supported by a Marie Curie Early Stage Initial Training Network Fellowship of the European Community’s Seventh Framework Program "PURESAFE". I wish to thank the supervisors and fellow research members of the project for the amazing support, fruitful interactions and training events. -
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. -
Learning for Microrobot Exploration: Model-Based Locomotion, Sparse-Robust Navigation, and Low-Power Deep Classification
Learning for Microrobot Exploration: Model-based Locomotion, Sparse-robust Navigation, and Low-power Deep Classification Nathan O. Lambert1, Farhan Toddywala1, Brian Liao1, Eric Zhu1, Lydia Lee1, and Kristofer S. J. Pister1 Abstract— Building intelligent autonomous systems at any Classification Intelligent, mm scale Fast Downsampling scale is challenging. The sensing and computation constraints Microrobot of a microrobot platform make the problems harder. We present improvements to learning-based methods for on-board learning of locomotion, classification, and navigation of microrobots. We show how simulated locomotion can be achieved with model- Squeeze-and-Excite Hard Activation System-on-chip: based reinforcement learning via on-board sensor data distilled Camera, Radio, Battery into control. Next, we introduce a sparse, linear detector and a Dynamic Thresholding method to FAST Visual Odometry for improved navigation in the noisy regime of mm scale imagery. Locomotion Navigation We end with a new image classifier capable of classification Controller Parameter Unknown Dynamics Original Training Image with fewer than one million multiply-and-accumulate (MAC) Optimization Modeling & Simulator Resulting Map operations by combining fast downsampling, efficient layer Reward structures and hard activation functions. These are promising … … SLIPD steps toward using state-of-the-art algorithms in the power- Ground Truth Estimated Pos. State Space limited world of edge-intelligence and microrobots. Sparse I. INTRODUCTION Local Control PID: K K K Microrobots have been touted as a coming revolution p d i for many tasks, such as search and rescue, agriculture, or Fig. 1: Our vision for microrobot exploration based on distributed sensing [1], [2]. Microrobotics is a synthesis of three contributions: 1) improving data-efficiency of learning Microelectromechanical systems (MEMs), actuators, power control, 2) a more noise-robust and novel approach to visual electronics, and computation. -
Robot Learning
Robot Learning 15-494 Cognitive Robotics David S. Touretzky & Ethan Tira-Thompson Carnegie Mellon Spring 2009 04/06/09 15-494 Cognitive Robotics 1 What Can Robots Learn? ● Parameter tuning, e.g., for a faster walk ● Perceptual learning: ALVINN driving the Navlab ● Map learning, e.g., SLAM algorithms ● Behavior learning; plans and macro-operators – Shakey the Robot (SRI) – Robo-Soar ● Learning from human teachers – Operant conditioning: Skinnerbots – Imitation learning 04/06/09 15-494 Cognitive Robotics 2 Lots of Work on Robot Learning ● IEEE Robotics and Automation Society – Technical Committee on Robot Learning – http://www.learning-robots.de ● Robot Learning Summer School – Lisbon, Portugal; July 20-24, 2009 ● Workshops at major robotics conferences – ICRA 2009 workshop: Approachss to Sensorimotor Learning on Humanoid Robots – Kobe, Japan; May 17, 2009 04/06/09 15-494 Cognitive Robotics 3 Parameter Optimization ● How fast can an AIBO walk? Figures from Kohl & Stone, ICRA 2004, for the ERS-210 model: – CMU (2002) 200 mm/s – German Team 230 mm/s Hand-tuned gaits – UT Austin Villa 245 mm/s – UNSW 254 mm/s – Hornsby (1999) 170 mm/s – UNSW 270 mm/s Learned gaits – UT Austin Villa 291 mm/s 04/06/09 15-494 Cognitive Robotics 4 Walk Parameters 12 parameters to optimize: ● Front locus (height, x pos, ypos) ● Rear locus (height, x pos, y pos) ● Locus length ● Locus skew multiplier (in the x-y plane, for turning) ● Height of front of body ● Height of rear of body From Kohl & Stone (ICRA 2004) ● Foot travel time ● Fraction of time foot is on ground 04/06/09 15-494 Cognitive Robotics 5 Optimization Strategy ● “Policy gradient reinforcement learning”: – Walk parameter assignment = “policy” – Estimate the gradient along each dimension by trying combinations of slight perturbations in all parameters – Measure walking speed on the actual robot – Optimize all 12 parameters simultaneously – Adjust parameters according to the estimated gradient. -
Systematic Review of Research Trends in Robotics Education for Young Children
sustainability Review Systematic Review of Research Trends in Robotics Education for Young Children Sung Eun Jung 1,* and Eun-sok Won 2 1 Department of Educational Theory and Practice, University of Georgia, Athens, GA 30602, USA 2 Department of Liberal Arts Education, Mokwon University, Daejeon 35349, Korea; [email protected] * Correspondence: [email protected]; Tel.: +1-706-296-3001 Received: 31 January 2018; Accepted: 13 March 2018; Published: 21 March 2018 Abstract: This study conducted a systematic and thematic review on existing literature in robotics education using robotics kits (not social robots) for young children (Pre-K and kindergarten through 5th grade). This study investigated: (1) the definition of robotics education; (2) thematic patterns of key findings; and (3) theoretical and methodological traits. The results of the review present a limitation of previous research in that it has focused on robotics education only as an instrumental means to support other subjects or STEM education. This study identifies that the findings of the existing research are weighted toward outcome-focused research. Lastly, this study addresses the fact that most of the existing studies used constructivist and constructionist frameworks not only to design and implement robotics curricula but also to analyze young children’s engagement in robotics education. Relying on the findings of the review, this study suggests clarifying and specifying robotics-intensified knowledge, skills, and attitudes in defining robotics education in connection to computer science education. In addition, this study concludes that research agendas need to be diversified and the diversity of research participants needs to be broadened. To do this, this study suggests employing social and cultural theoretical frameworks and critical analytical lenses by considering children’s historical, cultural, social, and institutional contexts in understanding young children’s engagement in robotics education. -
Multi-Leapmotion Sensor Based Demonstration for Robotic Refine Tabletop Object Manipulation Task
Available online at www.sciencedirect.com ScienceDirect CAAI Transactions on Intelligence Technology 1 (2016) 104e113 http://www.journals.elsevier.com/caai-transactions-on-intelligence-technology/ Original article Multi-LeapMotion sensor based demonstration for robotic refine tabletop object manipulation task* Haiyang Jin a,b,c, Qing Chen a,b, Zhixian Chen a,b, Ying Hu a,b,*, Jianwei Zhang c a Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China b Chinese University of Hong Kong, Hong Kong, China c University of Hamburg, Hamburg, Germany Available online 2 June 2016 Abstract In some complicated tabletop object manipulation task for robotic system, demonstration based control is an efficient way to enhance the stability of execution. In this paper, we use a new optical hand tracking sensor, LeapMotion, to perform a non-contact demonstration for robotic systems. A Multi-LeapMotion hand tracking system is developed. The setup of the two sensors is analyzed to gain a optimal way for efficiently use the informations from the two sensors. Meanwhile, the coordinate systems of the Mult-LeapMotion hand tracking device and the robotic demonstration system are developed. With the recognition to the element actions and the delay calibration, the fusion principles are developed to get the improved and corrected gesture recognition. The gesture recognition and scenario experiments are carried out, and indicate the improvement of the proposed Multi-LeapMotion hand tracking system in tabletop object manipulation task for robotic demonstration. Copyright © 2016, Chongqing University of Technology. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). -
Design and Control of a Large Modular Robot Hexapod
Design and Control of a Large Modular Robot Hexapod Matt Martone CMU-RI-TR-19-79 November 22, 2019 The Robotics Institute School of Computer Science Carnegie Mellon University Pittsburgh, PA Thesis Committee: Howie Choset, chair Matt Travers Aaron Johnson Julian Whitman Submitted in partial fulfillment of the requirements for the degree of Master of Science in Robotics. Copyright © 2019 Matt Martone. All rights reserved. To all my mentors: past and future iv Abstract Legged robotic systems have made great strides in recent years, but unlike wheeled robots, limbed locomotion does not scale well. Long legs demand huge torques, driving up actuator size and onboard battery mass. This relationship results in massive structures that lack the safety, portabil- ity, and controllability of their smaller limbed counterparts. Innovative transmission design paired with unconventional controller paradigms are the keys to breaking this trend. The Titan 6 project endeavors to build a set of self-sufficient modular joints unified by a novel control architecture to create a spiderlike robot with two-meter legs that is robust, field- repairable, and an order of magnitude lighter than similarly sized systems. This thesis explores how we transformed desired behaviors into a set of workable design constraints, discusses our prototypes in the context of the project and the field, describes how our controller leverages compliance to improve stability, and delves into the electromechanical designs for these modular actuators that enable Titan 6 to be both light and strong. v vi Acknowledgments This work was made possible by a huge group of people who taught and supported me throughout my graduate studies and my time at Carnegie Mellon as a whole. -
Machine Vision for Service Robots & Surveillance
Machine Vision for Service Robots & Surveillance Prof.dr.ir. Pieter Jonker EMVA Conference 2015 Delft University of Technology Cognitive Robotics (text intro) This presentation addresses the issue that machine vision and learning systems will dominate our lives and work in future, notably through surveillance systems and service robots. Pieter Jonker’s specialism is robot vision; the perception and cognition of service robots, more specifically autonomous surveillance robots and butler robots. With robot vision comes the artificial intelligence; if you perceive and understand, than taking sensible actions becomes relative easy. As robots – or autonomous cars, or … - can move around in the world, they encounter various situations to which they have to adapt. Remembering in which situation you adapted to what is learning. Learning comes in three flavors: cognitive learning through Pattern Recognition (association), skills learning through Reinforcement Learning (conditioning) and the combination (visual servoing); such as a robot learning from observing a human how to poor in a glass of beer. But as always in life this learning comes with a price; bad teachers / bad examples. 2 | 16 Machine Vision for Service Robots & Surveillance Prof.dr.ir. Pieter Jonker EMVA Conference Athens 12 June 2015 • Professor of (Bio) Mechanical Engineering Vision based Robotics group, TU-Delft Robotics Institute • Chairman Foundation Living Labs for Care Innovation • CEO LEROVIS BV, CEO QdepQ BV, CTO Robot Care Systems Delft University of Technology Content •