Publications by Aude Billard | EPFL Graph Search

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Language acquisition theories classically distinguish passive language understanding from active language production. However, recent findings show that brain areas such as Broca's region are shared in language understanding and production. Furthermore, th ...

Autonomous mobility devices such as transport, cleaning, and delivery robots, hold a massive economic and social benefit. However, their deployment should not endanger bystanders, particularly vulnerable populations such as children and older adults who ar ...

In order to facilitate and assist the indoor mobility of people with special needs, the classically static objects in the environment, such as furniture, can be rendered mobile. The need for efficient and safe autonomous coordination of a mobile furniture ...

Humans’ capacity to imitate has been extensively investigated through a wide-range of behavioral and developmental studies. Yet, despite the huge amount of phenomenological evidence gathered, we are still unable to relate this behavioral data to any specif ...

Efficient, adaptive and reliable visuomotor control system is crucial to enable robots to display flexibility in the face of changes in the environment. This paper takes inspiration in human eye-arm-hand coordination pattern to develop an equivalently robu ...

The sense of touch can provide a robot with a wealth of information about the contact region when interacting with an unknown environment. Nevertheless, utilizing touch information to plan exploration paths and adjust robot posture to improve task efficien ...

State-dependent dynamical systems (DSs) offer adaptivity, reactivity, and robustness to perturbations in motion planning and physical human-robot interaction tasks. Learning DS-based motion plans from non-linear reference trajectories is an active research ...

A current trend in robotics is to define robot tasks using a combination of superimposed motion patterns. For maximum versatility of such motion patterns, they should be easily and efficiently adaptable for situations beyond those for which the motion was ...

In this paper, we present an approach for learning a neural implicit signed distance function expressed in joint space coordinates, that efficiently computes distance-to-collisions for arbitrary robotic manipulator configurations. Computing such distances ...

Controlling complex tasks in robotic systems, such as circular motion for cleaning or following curvy lines, can be dealt with using nonlinear vector fields. This article introduces a novel approach called the rotational obstacle avoidance method (ROAM) fo ...

Object manipulation is a challenging task for robotics, as the physics involved in object interaction is complex and hard to express analytically. Here we introduce a modular approach for learning a manipulation strategy from human demonstration. Firstly w ...

Demonstration learning is a powerful and practical technique to develop robot behaviors. Even so, development remains a challenge and possible demonstration limitations, for example correspondence issues between the robot and demonstrator, can degrade poli ...

Human-object interaction is of great relevance for robots to operate in human environments. However, state-of-the-art robotic hands are far from replicating humans skills. It is, therefore, essential to study how humans use their hands to develop similar r ...

Performing shotcrete operations at construction sites can be hazardous to humans and inefficient. Robots can offer a safer and more efficient alternative to assist in these tasks. We present a new planning strategy for shotcrete robots, including both the spraying and surface finishing phases, that can plan for a general target area, whether flat or complexly curved. Our method uses learning from demonstrations and dynamical systems concepts to enable reactive and adaptive planning for robots, allowing them

Many manipulation tasks require coordinated motions for arm and fingers. Complexity increases when the task requires to control for the force at contact against a non-flat surface; This becomes even more challenging when this contact is done on a human. Al ...

Programming by demonstration (PbD) is a key research topic in robotics. It impacts both fundamental research and application-oriented studies.Work in that area tackles the development of robust algorithms for motor control, motor learning, gesture recognition and visuo-motor integration. While the field existed for more than 20 years, recent developments, taking inspiration in biological mechanisms of imitation, have brought a new perspective. Programming by demonstration, now, encompasses more of the learn

Our ability to grab, hold, and manipulate objects involves our dexterous hands, our sense of touch, and feedback from our eyes and muscles that allows us to maintain a controlled grip. Billard and Kragic review the progress made in robotics to emulate thes ...

This paper presents a biologically inspired approach to multimodal integration and decision-making in the context of human-robot interactions. More specifically, we address the principle of ideomotor compatibility by which observing the movements of others ...

Planning for a wide range of real-world 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 from expert demonstration. The majority of prior works limit themselves to learning simple linear constraints, or require strong knowledge of the true constraint parameterization or environmental model. To mitigate these problems, this paper presents a pos

Among the symptoms of schizophrenia, deficits in the recognition of intention is one of the most studied. However, there is no cognitive model of intention recognition that takes into account both innate and environmental/developmental factors. This work p ...

Aude Billard

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Social babbling: The emergence of symbolic gestures and words

Crash test-based assessment of injury risks for adults and children when colliding with personal mobility devices and service robots

A Dynamical System Approach to Decentralized Collision-free Autonomous Coordination of a Mobile Assistive Furniture Swarm

Parallel and Distributed Neural Models of the Ideomotor Principle: An Investigation of Imitative Cortical Pathways

Learning Coupled Dynamical Systems from Human Demonstration for Robotic Eye-Arm-Hand Coordination

Online active and dynamic object shape exploration with a multi-fingered robotic hand

Locally active globally stable dynamical systems: Theory, learning, and experiments

Learning to Control Planar Hitting Motions in a Monigolf-like Task

Neural Joint Space Implicit Signed Distance Functions for Reactive Robot Manipulator Control

Avoidance of Concave Obstacles Through Rotation of Nonlinear Dynamics

A modular approach to learning manipulation strategies from human demonstration

Tactile Guidance for Policy Adaptation

Hand-Object Interaction: From Human Demonstrations to Robot Manipulation

Human-Inspired Planning and Control of Shotcrete Robots based on Dynamical Systems Mapping

Arm-hand motion-force coordination for physical interactions with non-flat surfaces using dynamical systems: Toward compliant robotic massage

EDITORIAL: Robot Programming By Demonstration

Trends and challenges in robot manipulation

Biologically Inspired Multimodal Integration: Interferences in a Human-Robot Interaction Game

Learning Constraint Network from Demonstrations via Positive-Unlabeled Learning with Memory Replay

Influence of Saliency and Social Impairments on the Development of Intention Recognition