Publications by Aude Billard | EPFL Graph Search

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Many maneuvers of Unmanned Aerial Vehicles (UAV) can be considered within a framework of trajectory following. Though this issue can differ from one application to another, they all share the same problem of finding an optimal path (or signal) to perform the specified task. Finding this optimal trajectory is a challenging issue since it depends on both having an accurate mathematical model of the UAV, and designing the desired trajectory based on this dynamical model. %The former is usually tackled by estim

Objective. Translational studies on motor control and neurological disorders require detailed monitoring of sensorimotor components of natural limb movements in relevant animal models. However, available experimental tools do not provide a sufficiently ric ...

Robot Programming by Demonstration (PbD) aims at developing adaptive and robust controllers to enable the robot to learn new skills by observing and imitating a human demonstration. While the vast majority of PbD works focused on systems that learn a specific subset of tasks, our work explores the problem of recognition, generalization, and reproduction of tasks in a unified mathematical framework. The approach makes abstraction of the task and dataset at hand to tackle the general issue of learning which o

Performing manipulation tasks interactively in real environments requires a high degree of accuracy and stability. At the same time, when one cannot assume a fully deterministic and static environment, one must endow the robot with the ability to react rap ...

In this article, we propose an approach to extract variable-impedance during cutting tasks from human demonstrations, so as to ease soft-tissue cutting by robots. We model the dynamic adjustment of the human arm during interactions with the tissue and tran ...

Background The ability to follow one another's gaze plays an important role in our social cognition; especially when we synchronously perform tasks together. We investigate how gaze cues can improve performance in a simple coordination task (i.e., the mirr ...

Robust in-hand manipulation of objects with movable content requires estimation and prediction of the contents' motion with enough anticipation to allow time to compensate for resulting internal torques. The quick estimation of the objects' dynamics can be ...

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Dynamical Systems (DS) are fundamental to the modeling and understanding time evolving phenomena, and have application in physics, biology and control. As determining an analytical description of the dynamics is often difficult, data-driven approaches are ...

This work is part of the Aurora project which investigates the possible use of robots in therapy and education of children with autism (Aurora 2003), based on findings that people with autism enjoy interacting with computers, e.g. (Powell, 1996). In most of our trials we have been using mobile robots, e.g. (Dautenhahn and Werry, 2002). More recently we tested the use of a humanoid robotic doll. In (Dautenhahn and Billard, 2002) we reported on a first set of trials with 14 autistic subjects interacting with

We are interested in the question of human imitation and we address this through convergent evidence from neuroscience. The rationale of our work is that the nature of imitation deficits following brain lesion can unveil some of the neural and computational principles underlying normal imitation. In particular, we consider how imitation of meaningless gestures (i.e., hand postures relative to the head) is impaired in apraxia [1], i.e., an inability to perform voluntary movements that cannot be explained by

We present a novel, biologically inspired, approach to an efficient allocation of visual resources for humanoid robots in a form of a motor-primed visual attentional landscape. The attentional landscape is a more general, dynamic and a more complex concept ...

One of the hallmarks of physical interaction between humans is haptic communication, i.e. an informa- tion exchange through force signals. Humans excel in tasks that require such interaction by adapting impedance and anticipating the partner’s intentions. ...

This article presents a closed-form approach to constraining a flow within a given volume and around objects. The flow is guaranteed to converge and to stop at a single fixed point. The obstacle avoidance problem is inverted to enforce that the flow remain ...

Planning for diverse real-world robotic tasks necessitates to know and write all constraints. However, instances exist where these constraints are either unknown or challenging to specify accurately. A possible solution is to infer the unknown constraints ...

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 le ...

Tasks that require the cooperation of both hands and arms are common in human everyday life. Coordination helps to synchronize in space and temporally motion of the upper limbs. In fine bimanual tasks, coordination enables also to achieve higher degrees of ...

Imagine a world in which our furniture moves around like legged robots, interacts with us, and changes shape and function during the day according to our needs. This is the long term vision we have in the Roombots project. To work towards this dream, we ar ...

Bimanual fine-manipulation tasks demand the collaboration of both hands and rely on the coordinated forces applied by fingers from both hands. Despite the abundant degrees of freedom (DoFs) of our hands, humans distribute the roles across hands and apply b ...

Bringing robots as collaborative partners into homes presents various challenges to human-robot interaction. Robots will need to interact with untrained users in environments that are originally designed for humans. Compared to their industrial homologous ...

Aude Billard

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Learning and Control of UAV maneuvers Based on Demonstrations

A versatile robotic platform for the design of natural, three-dimensional reaching and grasping tasks in monkeys

Stochastic Gesture Production and Recognition Model for a Humanoid Robot

Coupled dynamical system based arm-hand grasping model for learning fast adaptation strategies

Learning From Demonstration and Interactive Control of Variable-Impedance to Cut Soft Tissues

Role of Gaze Cues in Interpersonal Motor Coordination: Towards Higher Affiliation in Human-Robot Interaction

A Predictive Model for Tactile Force Estimation Using Audio-Tactile Data

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Effects of repeated exposure of a humanoid robot on children with autism

Neurocomputational modeling of imitation deficits

Motor-Primed Visual Attention for Humanoid Robots

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

Avoiding Dense and Dynamic Obstacles in Enclosed Spaces: Application to Moving in Crowds

Positive-Unlabeled Constraint Learning for Inferring Nonlinear Continuous Constraints Functions From Expert Demonstrations

A structured prediction approach for robot imitation learning

An inverse optimization approach to understand human acquisition of kinematic coordination in bimanual fine manipulation tasks

Roombots: Reconfigurable Robots for Adaptive Furniture

Force Synergies Within and Across the Two Hands in Bimanual Skill Acquisition

A framework integrating statistical and social cues to teach a humanoid robot new skills