Publications by Aude Billard | EPFL Graph Search

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Skills that require the collaboration of both arms are common in humans’ everyday activities, and the coordination of upper limbs is key to human bimanual dexterity. The Skill Acquisition in Humans and Robots (ERC) project aims at obtaining a better understanding of the human skill acquisition process with a special focus on bimanual dexterous manipulation tasks, so as to develop novel robotic controllers resulting in the same level of precision and robustness. We conduct a longitudinal study of the acquisi

In this abstract, we combine work from [Lagarde et al., 2010] and [Calinon et al., 2009] for learning and reproduction of, respectively, navigation tasks on a mobile robot and gestures with a robot arm. Both approaches build a sensory motor map under human guidance to learn the desired behavior. With several actions possible at the same time, the selec- tion of action becomes a real issue. Several solutions exist to this problem : hi- erarchical architecture, parallel modules including subsumption architect

Catching a fast flying object is particularly challenging as consists of two tasks: it requires extremely precise estimation of the object’s motion and control of the robot motion. Any small imprecision may lead the fingers to close too abruptly and let the object fly away from the hand before closing. We present a strategy to overcome for sensori- motor imprecision by introducing softness in the catching approach. Soft catching consists of having the robot moves with the object for a short period of time,

We propose a new benchmarking protocol to evaluate algorithms for bimanual robotic manipulation semi-deformable objects. The benchmark is inspired from two real-world applications: (a) watchmaking craftsmanship, and (b) belt assembly in automobile engines. ...

We investigate the role of obstacle avoidance in visually guided reaching and grasping movements. We report on a human study in which subjects performed prehensile motion with obstacle avoidance where the position of the obstacle was systematically varied ...

This paper presents a method for learning discrete robot motions from a set of demonstrations. We model a motion as a nonlinear autonomous (i.e. time-invariant) Dynamical System (DS), and define sufficient conditions to ensure global asymptotic stability a ...

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. We propose an approach ...

We present a probabilistic approach to learn robust models of human motion through imitation. The association of Hidden Markov Model (HMM), Gaussian Mixture Regression (GMR) and dynamical systems allows us to extract redundancies across multiple demonstrations and build time-independent models to reproduce the dynamics of the demonstrated movements. The approach is first systematically evaluated and compared with other approaches by using generated trajectories sharing similarities with human gestures. Thre

This month, the IEEE Robotics and Automation Society (RAS) will celebrate 40 years of its flagship conference, the IEEE International Conference on Robotics and Automation (ICRA), with a special edition named ICRA@40. This unique event will be held from 23 to 26 September 2024 in Rotterdam, The Netherlands. ICRA@40 will feature more than 60 plenary talks by the most renowned scientists and industry leaders in the field of robotics and automation. These talks will provide invaluable insights into the latest

This paper presents a closed-form approach to obstacle avoidance for multiple moving convex and star-shaped concave obstacles. The method takes inspiration in harmonic-potential fields. It inherits the convergence properties of harmonic potentials. We prov ...

In this letter, we propose a real-time self-collision avoidance approach for whole-body humanoid robot control. To achieve this, we learn the feasible regions of control in the humanoid's joint space as smooth self-collision boundary functions. Collision-f ...

A head-mounted camera was used to measure head direction. The camera was mounted to the forehead of 20 6- and 20 12-month-old infants while they watched an object held at 11 horizontal (-80 degrees to + 80 degrees) and 9 vertical (-48 degrees to + 50 degre ...

During reach-to-grasp motions,the Electromyographic (EMG) activity of the arm varies depending on motion stage. The variability of the EMG signals results in low classification accuracy during the reaching phase, delaying the activation of the prosthesis. ...

In the context of object interaction and manipulation, one characteristic of a robust grasp is its ability to comply with external perturbations applied to the grasped object while still maintaining the grasp. In this work we introduce an approach for gras ...

Robots come into physical contact with humans in both experimental and operational settings. Many potential factors motivate the detection of human contact, ranging from safe robot operation around humans, to robot behaviors that depend on human guidance. ...

This work investigates whether population vector coding, a distributed computational paradigm, could be a principle mechanism for performing sensorimotor and frames of reference transformations. This paper presents a multilayer neural network that can perf ...

Many manipulations in human everyday activities rely on the collaboration of our two hands. Bimanual fine manipulation tasks are particularly demanding when precise coordination among fingers of both hands are required. Yet, despite the abundant degrees of ...

Many daily life tasks require precise control when making contact with surfaces. Ensuring a smooth transition from free motion to contact is crucial as incurring a large impact force may lead to unstable contact with the robot bouncing on the surface, i.e. ...

This paper presents an experiment in which the iCub humanoid robot learns to recognize faces through proprioceptive information. We take inspiration in the way blind people recognize people's faces, i.e. through tactile exploration of the person's face. Th ...

The processing of biological motion is a critical, everyday task performed with remarkable efficiency by human sensory systems. Interest in this ability has focused to a large extent on biological motion processing in the visual modality (see, for example, ...

Aude Billard

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Towards Understanding of Human Kinematic Coordination Patterns in Bimanual Fine Manipulation Tasks

A state-action neural network supervising navigation and manipulation behaviors for complex task reproduction

A Dynamical System Approach for Catching Softly a Flying Object: Theory and Experiment

Benchmark for Bimanual Robotic Manipulation of Semi-deformable Objects

Learning robotic eye–arm–hand coordination from human demonstration: a coupled dynamical systems approach

Learning Stable Non-Linear Dynamical Systems with Gaussian Mixture Models

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

A learning by imitation model handling multiple constraints and motion alternatives

Anniversaries Are a Good Time to Reflect on the Past, Present, and Future of Robotics and Automation

Avoidance of Convex and Concave Obstacles with Convergence ensured through Contraction

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Using a head-mounted camera to infer attention direction

Reach-to-grasp motions: Towards a dynamic classification approach for upper-limp prosthesis

Iterative Learning of Grasp Adaptation through Human Corrections

A Survey of Tactile Human-Robot Interactions

Three Dimensional Frames of References Transformations using Recurrent Populations of Neurons

Effects of Task Conditions on Human Hand Pose Selection Strategies in a Bimanual Fine Manipulation Task

A Dynamical System Based Approach for Controlling Robotic Manipulators During Non-contact/Contact Transitions

Face classification using touch with a humanoid robot hand

Auditory motion affects visual biological motion processing