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Motion learning and Adaptive Impedance for Robot Control during Physical Interaction with Humans

Motion Learning and Adaptive Impedance for Robot Control dur...

引用

2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Elena Gribovskaya Aude Billard Abderrahmane Kheddar Learning Algorithms and Systems Laboratory (LASA) EPFLSwitzerland CNRS-UM2 LIRMM MontpellierFranceand the CNRS-AIST JRLUMI3218/CRTJapan

This article combines programming by demon- stration and adaptive control for teaching a robot to physically interact with a human in a collaborative task requiring sharing of a load by the two partners. learning a task model allows the robot to anticipate the partner’s intentions and adapt its motion according to perceived forces. As the human represents a highly complex contact environment, direct reproduction of the learned model may lead to sub-optimal results. To compen- sate for unmodelled uncertainties, in addition to learning we propose an adaptive control algorithm that tunes the impedance parameters, so as to ensure accurate reproduction. To facilitate the illustration of the concepts introduced in this paper and provide a systematic evaluation, we present experimental results obtained with simulation of a dyad of two planar 2-DOF robots.

关键词： Impedance Force Adaptation models Robot kinematics Kinematics Humans

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Policy adaptation with tactile feedback

Policy adaptation with tactile feedback

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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Brenna D. Argall Eric L. Sauser Aude G. Billard Learning Algorithms and Systems Laboratory (LASA) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland

Behavior adaptation with execution experience is a practical feature for any policy learning system. Our work provides performance feedback to a robot learner in the form of tactile corrections from a human teacher, for the purpose of policy refinement as well as policy reuse. Multiple variants of our general approach have been validated on the iCub robot, as building blocks towards a high-DoF humanoid system that integrates tactile sensing on the hands and arms into complex behaviors and sophisticated learning routines.

关键词： Humans Adaptation models Tactile sensors Laboratories

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Tactile guidance for policy refinement and reuse

Tactile guidance for policy refinement and reuse

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IEEE International Conference on Development and learning, ICDL

作者： Brenna D. Argall Eric L. Sauser Aude G. Billard Learning Algorithms and Systems Laboratory (LASA) École Polytechnique Fédérale de Lausanne Lausanne Switzerland

Demonstration learning is a powerful and practical technique to develop robot behaviors. Even so, development remains a challenge and possible demonstration limitations can degrade policy performance. This work presents an approach for policy improvement and adaptation through a tactile interface located on the body of a robot. We introduce the Tactile Policy Correction (TPC) algorithm, that employs tactile feedback for the refinement of a demonstrated policy, as well as its reuse for the development of other policies. We validate TPC on a humanoid robot performing grasp-positioning tasks. The performance of the demonstrated policy is found to improve with tactile corrections. Tactile guidance also is shown to enable the development of policies able to successfully execute novel, undemonstrated, tasks.

关键词： Humans Robot kinematics Manipulators Tactile sensors Joints

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learning collaborative manipulation tasks by demonstration using a haptic interface

Learning collaborative manipulation tasks by demonstration u...

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International Conference on Advanced Robotics (ICAR)

作者： Sylvain Calinon Paul Evrard Elena Gribovskaya Aude Billard Abderrahmane Kheddar Learning Algorithms and Systems Laboratory (LASA) Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland UMI3218/CRT CNRS-AIST JRL Tsukuba Japan

This paper presents a method by which a robot can learn through observation to perform a collaborative manipulation task, namely lifting an object. The task is first demonstrated by a user controlling the robot's hand via a haptic interface. learning extracts statistical redundancies in the examples provided during training by using Gaussian Mixture Regression and Hidden Markov Model. Haptic communication reflects more than pure dynamic information on the task, and includes communication patterns, which result from the two users constantly adapting their hand motion to coordinate in time and space their respective motions. We show that the proposed statistical model can efficiently encapsulate typical communication patterns across different dyads of users, that are stereotypical of collaborative behaviours between humans and robots. The proposed learning approach is generative and can be used to drive the robot's retrieval of the task by ensuring a faithful reproduction of the overall dynamics of the task, namely by reproducing the force patterns for both lift the object and adapt to the human user's hand motion. This work shows the potential that teleoperation holds for transmitting both dynamic and communicative information on the task, which classical methods for programming by demonstration have traditionally overlooked.

关键词： Collaboration Haptic interfaces Robot kinematics Hidden Markov models Humans Orbital robotics Dynamic programming Robot control Communication system control Data mining

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Evaluating the ICRA 2008 HRI challenge

Evaluating the ICRA 2008 HRI challenge

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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Astrid Weiss Thomas Scherndl Manfred Tscheligi Aude Billard ICT&S Center University of Salzburg Salzburg Austria Learning Algorithms and Systems Laboratory LASA School of Engineering Lausanne Switzerland

This paper reports on the evaluation of the ICRA 2008 Human-Robot Interaction (HRI) Challenge. Five research groups demonstrated state-of-the-art work on HRI with a special focus on social and learning abilities. The demonstrations were rated by expert evaluators, in charge of awarding the prize, and 269 participants, i.e. 20 percent of the conference attendees through a standardized questionnaire (semantic differential). The data was analyzed with respect to six independent variables: expert evaluators vs. attendees, nationality of participants, origin region of the demo, age, gender and knowledge level of the attendees. Conference attendees tended to give higher scores for Social Skills, General Impression, and Overall Score than the expert evaluators. Irrespectively of the level of knowledge, age, and gender, conference attendees rated all demos relatively homogeneously. However, a comparative analysis of the conference attendees's ratings nationality-wise showed that demonstrations were rated differently depending on the region of origin. Conference attendees for the USA and Asian countries tended to rate demos from the same country of origin more frequently and more positively.

关键词： Robots Europe Educational institutions Conferences Automation Humans Asia

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Roombots-mechanical design of self-reconfiguring modular robots for adaptive furniture

Roombots-mechanical design of self-reconfiguring modular rob...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Alexander Sproewitz Aude Billard Pierre Dillenbourg Auke Jan Ijspeert Bio-Inspired Robotics Group (BIRG) École Polytechnique Fédérale de Lausanne Lausanne Switzerland Learning Algorithms and Systems Laboratory (LASA) École Polytechnique Fédérale de Lausanne Lausanne Switzerland Centre de Recherche et d'Appui pour la Formation (CRAFT) École Polytechnique Fédérale de Lausanne Lausanne Switzerland

We aim at merging technologies from information technology, roomware, and robotics in order to design adaptive and intelligent furniture. This paper presents design principles for our modular robots, called Roombots, as future building blocks for furniture that moves and self-reconfigures. The reconfiguration is done using dynamic connection and disconnection of modules and rotations of the degrees of freedom. We are furthermore interested in applying Roombots towards adaptive behaviour, such as online learning of locomotion patterns. To create coordinated and efficient gait patterns, we use a Central Pattern Generator (CPG) approach, which can easily be optimized by any gradient-free optimization algorithm. To provide a hardware framework we present the mechanical design of the Roombots modules and an active connection mechanism based on physical latches. Further we discuss the application of our Roombots modules as pieces of a homogenic or heterogenic mix of building blocks for static structures.

关键词： Robot kinematics Intelligent robots Robotics and automation Hardware Pervasive computing Robotic assembly Merging Information technology Ubiquitous computing Augmented reality

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Evaluating the ICRA 2008 HRI challenge

Evaluating the ICRA 2008 HRI challenge

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4th ACM/IEEE International Conference on Human-Robot Interaction, HRI'09

作者： Weiss, Astrid Scherndl, Thomas Tscheligi, Manfred Billard, Aude ICTandS Center University of Salzburg Sigmund-Haffner-Gasse 18 5020 Salzburg Austria Learning Algorithms and Systems Laboratory - LASA School of Engineering - EPFL Station 9 - 1015 Lausanne Switzerland

ISBN: (纸本)9781605584041

This paper reports on the evaluation of the ICRA 2008 Human-Robot Interaction (HRI) Challenge. Five research groups demonstrated state-of-the-art work on HRI with a special focus on social and learning abilities. The demonstrations were rated by expert evaluators, in charge of awarding the prize, and 269 participants, i.e. 20 percent of the conference attendees through a standardized questionnaire (semantic dierential). The data was analyzed with respect tosix independent variables: expert evaluators vs. attendees,nationality of participants, origin region of the demo, age,gender and knowledge level of the attendees. Conference attendees tended to give higher scores for Social Skills, General Impression, and Overall Score than the expert evaluators. Irrespectively of the level of knowledge, age, and gender, conference attendees rated all demos relatively homogeneously. However, a comparative analysis of the conference attendees's ratings nationality-wise showed that demonstrations were rated differently depending on the region of origin. Conference attendees for the USA and Asian countries tended to rate demos from the same country of origin more frequently and more positively.

关键词： Human robot interaction

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A Probabilistic Programming by Demonstration Framework Handling Constraints in Joint Space and Task Space

A Probabilistic Programming by Demonstration Framework Handl...

引用

2008 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS 2008), vol.1

作者： Sylvain Calinon Aude Billard Learning Algorithms and Systems Laboratory (LASA) Ecole Polytechnique Federale de Lausanne Lausanne Switzerland

We present a probabilistic architecture for solving generically the problem of extracting the task constraints through a Programming by Demonstration (PbD) framework and for generalizing the acquired knowledge to various situations. In previous work, we proposed an approach based on Gaussian Mixture Regression (GMR) to find a controller for the robot reproducing the essential characteristics of a skill in joint space and in task space through Lagrange optimization. In this paper, we extend this approach to a more generic procedure handling simultaneously constraints in joint space and in task space by combining directly the probabilistic representation of the task constraints with a simple Jacobian-based inverse kinematics solution. Experiments with two 5-DOFs Katana robots are presented with manipulation tasks that consist of handling and displacing a set of objects.

关键词： Joints Aerospace electronics Robots Trajectory Glass Kinematics Jacobian matrices

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Neurocomputational modeling of imitation deficits

引用

BMC Neuroscience 2008年第1期9卷 1-1页

作者： Biljana Petreska Aude G Billard Learning Algorithms and Systems Laboratory (LASA) Ecole Polytechnique Fédérale de Lausanne (EPFL) CH-1015 Lausanne Switzerland

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Graph Signature for Self-Reconfiguration Planning

Graph Signature for Self-Reconfiguration Planning

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2008 IEEE/RSJ International Conference on Intelligent Robots and systems, Pages 526-1042

作者： Masoud Asadpour Alexander Sproewitz Aude Billard Pierre Dillenbourg Auke Jan Ijspeert ECE Dept. University of Tehran Control and Intelligent Processing Center of Excellence Iran Bio-Inspired Robotics Group (BIRG) Switzerland Learning Algorithms and Systems Laboratory (LASA) Switzerland Centre de Recherche et d Appui pour la Formation Switzerland Centre de Recherche et d'Appui pour la Formation (CRAFT) Ecole Polytechnique Fédérale de Lausanne (EPFL) Switzerland Bio-Inspired Robotics Group (BIRG)

ISBN: (纸本)9781424420575

This project incorporates modular robots as building blocks for furniture that moves and self-reconfigures. The reconfiguration is done using dynamic connection/disconnection of modules and rotations of the degrees of freedom. This paper introduces a new approach to self-reconfiguration planning for modular robots based on the graph signature and the graph edit-distance. The method has been tested in simulation on two type of modules: YaMoR and M-TRAN. The simulation results shows interesting features of the approach, namely rapidly finding a near-optimal solution.

关键词： Modular self-reconfigurable robots Adaptive furniture Graph isomorphism Graph signature Graph edit distance Modular robots graph editing Line graph Reconfiguration Furnishings signatures Building blocks Degree of freedom crop rotation

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