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IEEE International Conference on Robotics and Automation (ICRA)

作者： Amir Firouzeh Seyed Sina Mirrazavi Salehian Aude Billard Jamie Paik Amir Firouzeh and Jamie paik are with Reconfigurable Robotics Lab at EPFL Lausanne Ecole Polytechnique Federale de Lausanne Lausanne VD CH Seyed Sina Mirrazavi Salehian and Aude Billard are with Learning Algorithms and Systems Laboratory at EPFL Lausanne

ISBN: (纸本)9781479969241

Various robotic applications including surgical instruments, wearable robots and autonomous mobile robots are often constrained with strict design requirements on high degrees of freedom (DoF) and minimal volume and weight. An intuitive design to meet these contradictory requirements is to embed locking mechanism in under actuated robotic manipulators to direct the actuation from a single and remote source to drive different joints on demand. Mechanical clutches do serve such purposes but often are bulky and require auxiliary mechanism making it difficult to justify the high cost adding the additional DoF, especially in cm scale. Here, we introduce an under-actuated robotic arm with shape memory polymer (SMP) joints. Through controlling the temperature, the stiffness of the joints can be adjusted and selected joints will be activated while the rest are fixed in their position. The presented prototype can control the joints independently with a coupled actuation from two stepper motors. Since we have redundant DoFs in the arm, there can be more than one configuration to reach a given position. We use a probabilistic technique to determine the optimum configuration with the minimum number of active joints that can yield the desired posture. In this paper, we report on the performance of the proposed design for the hardware and the configuration planner.

关键词： Joints Robots Heating Polymers Tendons Shape Temperature

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learning Barrier-Certified Polynomial Dynamical systems for Obstacle Avoidance with Robots

Learning Barrier-Certified Polynomial Dynamical Systems for ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Martin Schonger Hugo T. M. Kussaba Lingyun Chen Luis Figueredo Abdalla Swikir Aude Billard Sami Haddadin Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich (TUM) Germany School of Computer Science University of Nottingham UK Omar Al-Mukhtar University (OMU) Albaida Libya Learning Algorithms and Systems Laboratory EPFL Switzerland

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Established techniques that enable robots to learn from demonstrations are based on learning a stable dynamical system (DS). To increase the robots’ resilience to perturbations during tasks that involve static obstacle avoidance, we propose incorporating barrier certificates into an optimization problem to learn a stable and barrier-certified DS. Such optimization problem can be very complex or extremely conservative when the traditional linear parameter-varying formulation is used. Thus, different from previous approaches in the literature, we propose to use polynomial representations for DSs, which yields an optimization problem that can be tackled by sum-of-squares techniques. Finally, our approach can handle obstacle shapes that fall outside the scope of assumptions typically found in the literature concerning obstacle avoidance within the DS learning framework. Supplementary material can be found at the project webpage: https://***/abc-ds

关键词： Shape Scalability Perturbation methods Polynomials Collision avoidance Dynamical systems Task analysis

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Evaluation of an Industrial Robotic Assistant in an Ecological Environment

Evaluation of an Industrial Robotic Assistant in an Ecologic...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Baptiste Busch Giuseppe Cotugno Mahdi Khoramshahi Grigorios Skaltsas Dario Turchi Leonardo Urbano Mirko Wächter You Zhou Tamim Asfour Graham Deacon Duncan Russell Aude Billard EPFL Learning Algorithms and Systems Laboratory (LASA) Lausanne Switzerland Robotics Research Group of Ocado Technology Hatfield UK University of Hertfordshire Hatfield UK KIT High Performance Humanoid Technologies Lab (H2T) Karlsruhe Germany

Social robotic assistants have been widely studied and deployed as telepresence tools or caregivers. Evaluating their design and impact on the people interacting with them is of prime importance. In this research, we evaluate the usability and impact of ARMAR-6, an industrial robotic assistant for maintenance tasks. For this evaluation, we have used a modified System Usability Scale (SUS) to assess the general usability of the robotic system and the Godspeed questionnaire series for the subjective perception of the coworker. We have also recorded the subjects' gaze fixation patterns and analyzed how they differ when working with the robot compared to a human partner.

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Teaching physical collaborative tasks: object-lifting case study with a humanoid

Teaching physical collaborative tasks: object-lifting case s...

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IEEE-RAS International Conference on Humanoid Robots

作者： Paul Evrard Elena Gribovskaya Sylvain Calinon Aude Billard Abderrahmane Kheddar CNRS-UM2 LIRMM Centre National de la Recherche Scientifique (CNRS) Montpellier France UMI3218/CRT CNRS-AIST JRL Tsukuba Japan Learning Algorithms and Systems Laboratory Switzerland Italian Institute of Technology Italy

ISBN: (纸本)9781424445875

This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the haptic communication process that takes place during physical collaborative tasks can be encapsulated by the probabilistic model. This framework encodes the dataset in a Gaussian Mixture Model, which components represent the local correlations across the variables that characterize the task. A set of demonstrations is performed using a bilateral coupling teleoperation setup; then the statistical model is trained in a pure follower/leader role distribution mode between the human and robot alternatively. The task is reproduced using Gaussian Mixture Regression. We present the probabilistic model and the experimental results obtained on the humanoid platform HRP-2; preliminary results assess our theory on switching behavior modes in dyad collaborative tasks: when reproduced with users which were not instructed to behave in either a follower or a leader mode, the robot switched automatically between the learned leader and follower behaviors.

关键词： Education Collaboration

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Action Anticipation: Reading the Intentions of Humans and Robots

arXiv

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arXiv 2018年

作者： Duarte, Nuno Raković, Mirko Tasevski, Jovica Coco, Moreno Billard, Aude Santos-Victor, José The Vislab Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Portugal The Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia The Department of Psychology Centre for Cognitive Ageing and Cognitive Epidemiology University of Edinburgh United Kingdom The Learning Algorithms and Systems Laboratory School of Engineering Epfl Lausanne Switzerland

Humans have the fascinating capacity of processing non-verbal visual cues to understand and anticipate the actions of other humans. This "intention reading" ability is underpinned by shared motor-repertoires and action-models, which we use to interpret the intentions of others as if they were our own. We investigate how the different cues contribute to the legibility of human actions during interpersonal interactions. Our first contribution is a publicly available dataset with recordings of human body-motion and eye-gaze, acquired in an experimental scenario with an actor interacting with three subjects. From these data, we conducted a human study to analyse the importance of the different non-verbal cues for action perception. As our second contribution, we used the motion/gaze recordings to build a computational model describing the interaction between two persons. As a third contribution, we embedded this model in the controller of an iCub humanoid robot and conducted a second human study, in the same scenario with the robot as an actor, to validate the model's "intention reading" capability. Our results show that it is possible to model (non-verbal) signals exchanged by humans during interaction, and how to incorporate such a mechanism in robotic systems with the twin goal of : (i) being able to "read" human action intentions, and (ii) acting in a way that is legible by humans. Copyright © 2018, The Authors. All rights reserved.

关键词： Anthropomorphic robots

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The DoF-Box Project: An Educational Kit for Configurable Robots

The DoF-Box Project: An Educational Kit for Configurable Rob...

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2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Pages 805-1210

作者： D. Daidie O. Barbey A. Guignard D. Roussy F. Guenter A. Ijspeert A. Billard Learning Algorithms and Systems Laboratory (LASA) School of engineering Ecole Polytechnique Federale de Lausanne (EPFL) 1015 Lausanne Switzerland

ISBN: (纸本)9781424412631;1424412633

This paper describes the DoF-Box, a modular, reconfigurable robot, used in Hands-on practicals of robotics taught to microengineering students. We present the hardware and software of the robots and describe the pedagogical approach adopted in the practicals. This approach encourages the creativity and imagination of the students, while ensuring that the students put in practice fundamental laws of control they are taught in class. Some of the results, including particular design of robots, obtained by the students are also shown.

关键词： Robot Students Imagination configurability robotics Computer hardware Reconfigurable robot Hand computer software

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Reaching and grasping kitchenware objects

Reaching and grasping kitchenware objects

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IEEE/SICE International Symposium on System Integration

作者： Rui Figueiredo Ashwini Shukla Duarte Aragão Plinio Moreno Alexandre Bernardino José Santos-Victor Aude Billard Faculty of Electrical and Computer Engineering Institute de Sistemas e Robótica Instituto Superior Técnico Lisbon Portugal Learning Algorithms and Systems Laboratory STI-I2S-LASA École Polytechnique Fédérale de Lausanne Lausanne Switzerland

We integrate software components that allow efficient and successful grasping of kitchenware objects. The contributed components include: The object pose detector, the gripper reaching motion and the grasp hypothesis selection. The object pose detector of Drost et. al. [10] is improved, considering rotationally symmetric objects. The reaching motion execution combines two independent dynamical systems: The approach direction system and its tangent space [21]. The coupling provides a robust reaching component that copes with several gripper configurations. The grasp hypothesis selection filters the object poses by considering the table orientation.

关键词： Grasping Computational modeling Grippers Detectors Couplings Trajectory Heuristic algorithms

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On the Influence of Emotional Feedback on Emotion Awareness and Gaze Behavior

On the Influence of Emotional Feedback on Emotion Awareness ...

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International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII

作者： Fabien Ringeval Andreas Sonderegger Basilio Noris Aude Billard Juergen Sauer Denis Lalanne Document Image and Voice Analysis group University of Fribourg Fribourg Switzerland Universite de Fribourg Fribourg FR CH Learning Algorithms and Systems Laboratory Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Cognitive Ergonomic group University of Fribourg Fribourg Switzerland

This paper examines how emotion feedback influences emotion awareness and gaze behavior. Simulating a videoconference setup, 36 participants watched 12 emotional video sequences that were selected from the SEMAINE database. All participants wore an eye-tracker to measure gaze behavior and were asked to rate the perceived emotion for each video sequence. 3 conditions were tested: (c1) no feedback, i.e., the original video-sequences, (c2) correct feedback, i.e., an emoticon is integrated in the video to show the emotion depicted by the person in the video and (c3) random feedback, i.e., the emoticon displays at random an emotional state that may or may not correspond to the one of the person. The results showed that emotion feedback had a significant influence on gaze behavior, e.g., over time random feedback led to a decrease in the frequency of episodes of gaze. No effect of emotion display was observed for emotion recognition. However, experiments on the automatic emotion recognition using gaze behavior provided good performance, with better score on arousal than valence, and a very good performance was obtained in the automatic recognition of the correctness of the emotion feedback.

关键词： Emotion recognition Databases Estimation Mood Cameras Educational institutions Teamwork

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A Structured Prediction Approach for Robot Imitation learning

arXiv

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arXiv 2023年

作者： Duan, Anqing Batzianoulis, Iason Camoriano, Raffaello Rosasco, Lorenzo Pucci, Daniele Billard, Aude Robotics and Machine Intelligence Laboratory The Hong Kong Polytechnic University Hong Kong Learning Algorithms and Systems Laboratory École Polytechnique Fédérale de Lausanne Lausanne Switzerland Visual And Multimodal Applied Learning Laboratory Politecnico di Torino Turin Italy DIBRIS Università degli Studi di Genova Genoa Italy Laboratory for Computational and Statistical Learning IIT@MIT Istituto Italiano di Tecnologia Massachusetts Institute of Technology CambridgeMA United States Center Università di Genova Genoa Italy Dynamic Interaction Control research line Italian Institute of Technology Genoa Italy

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised learning that enables learning models to operate on output spaces with complex structures. Through the lens of structured prediction, we show how robots can learn to imitate trajectories belonging to not only Euclidean spaces but also Riemannian manifolds. Exploiting ideas from information theory, we propose a class of loss functions based on the f-divergence to measure the information loss between the demonstrated and reproduced probabilistic trajectories. Different types of f-divergence will result in different policies, which we call imitation modes. Furthermore, our approach enables the incorporation of spatial and temporal trajectory modulation, which is necessary for robots to be adaptive to the change in working conditions. We benchmark our algorithm against state-of-the-art methods in terms of trajectory reproduction and adaptation. The quantitative evaluation shows that our approach outperforms other algorithms regarding both accuracy and efficiency. We also report real-world experimental results on learning manifold trajectories in a polishing task with a KUKA LWR robot arm, illustrating the effectiveness of our algorithmic framework. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

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Control Interface for Hands-free Navigation of Standing Mobility Vehicles based on Upper-Body Natural Movements

Control Interface for Hands-free Navigation of Standing Mobi...

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2020 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Yang Chen Diego Paez-Granados Hideki Kadone Kenji Suzuki School of Integrative and Global Majors (SIGMA) University of Tsukuba Japan Learning Algorithms and Systems Laboratory (LASA) Ecole Polytechnique Federale de Lausanne (EPFL) Lausanne Switzerland Center for Innovative Medicine and Engineering University of Tsukuba Hospital Japan Faculty of Engineering and Center for Cybernics Research University of Tsukuba Japan

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

In this paper, we propose and evaluate a novel human-machine interface (HMI) for controlling a standing mobility vehicle or person carrier robot, aiming for a hands-free control through upper-body natural postures derived from gaze tracking while walking. We target users with lower-body impairment with remaining upper-body motion capabilities. The developed HMI bases on a sensing array for capturing body postures; an intent recognition algorithm for continuous mapping of body motions to robot control space; and a personalizing system for multiple body sizes and shapes. We performed two user studies: first, an analysis of the required body muscles involved in navigating with the proposed control; and second, an assessment of the HMI compared with a standard joystick through quantitative and qualitative metrics in a narrow circuit task. We concluded that the main user control contribution comes from Rectus Abdominis and Erector Spinae muscle groups at different levels. Finally, the comparative study showed that a joystick still outperforms the proposed HMI in usability perceptions and controllability metrics, however, the smoothness of user control was similar in jerk and fluency. Moreover, users' perceptions showed that hands-free control made it more anthropomorphic, animated, and even safer.

关键词： Measurement Legged locomotion Navigation Muscles Robot sensing systems Usability Task analysis

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