Publications de Aude Billard | EPFL Graph Search

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We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...

Robot programming by demonstration (RPD) covers methods by which a robot learns new skills through human guidance. We present an interactive, multimodal RPD framework using active teaching methods that places the human teacher in the robot's learning loop. ...

We present a generic framework that combines Dynamical Systems movement control with Programming by Demon- stration (PbD) to teach a robot bimanual coordination task. The model consists of two systems: a learning system that processes data collected during ...

A non-obtrusive portable device, wearable from infancy through adulthood, mounted with i) a set of two or more optical device(s) providing visual and audio information as perceived by the user ii) an actuated mirror or optical device returning visual infor ...

Gripper adaptability to handle objects of different shape and size brings high flexibility to manipulation. Gripping flat, round, or narrow objects poses challenges to even the most sophisticated robotic grippers. Among various gripper technologies, the va ...

Background: Active upper-limb prostheses are used to restore important hand functionalities, such as grasping. In conventional approaches, a pattern recognition system is trained over a number of static grasping gestures. However, training a classifier in ...

Purpose - The purpose of this study is to develop a robotic training system for the hand movements during manual welding. The system provides real-time notice-feedback with sound or light alarms, whenever the welding hand vibrates beyond the nominal level ...

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...

This paper explores the potential of surgeons to perform solo laparoscopic anastomosis by introducing an innovative approach that uses feet-driven supernumerary robotic manipulation. This system allows surgeons to effectively and intuitively perform coordinated four-handed manipulation over two robotic arms. In a quasi-real-world medical scenario, a behavioral investigation is carried out to assess the feasibility and usability of the system during laparoscopic anastomosis performed by professional surgeons

The goal of developing algorithms for programming robots by demonstration is to create an easy way of programming robots that can be accomplished by everyone. When a demonstrator teaches a task to a robot, he/she shows some ways of fulfilling the task, but ...

In a human robot interaction scenario, predicting the human motion intention is essential for avoiding inconvenient delays and for a smooth reactivity of the robotic system. In particular, when dealing with hand prosthetic devices, an early estimation of t ...

Many tasks require the robot to enter in contact with surfaces, be it to take support, to polish or to grasp an object. It is crucial that the robot controls forces both upon making contact and while in contact. While many solutions exist to control for co ...

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 b ...

Human motion studies have focused primarily on modeling straight point-to-point reaching movements. However, many goal-directed reaching movements, such as movements directed towards oneself, are not straight but rather follow highly curved trajectories. T ...

The real-time estimation through vision of the physical properties of objects manipulated by humans is important to inform the control of robots for performing accurate and safe grasps of objects handed over by humans. However, estimating the 3D pose and d ...

In many tasks such as finishing operations, achieving accurate force tracking is essential. However, uncertainties in the robot dynamics and the environment limit the force tracking accuracy. Learning a compensation model for these uncertainties to reduce ...

Cognitive information has been exploited in non-invasive Brain Computer Interface (BCI) scenarios to provide autonomous external agents with additional information. In this context, Error-related potentials (ErrPs), temporal deflections in electroencephalo ...

Autonomous dynamical systems (DS) has emerged as an extremely flexible and powerful method for modeling robotic tasks. Task execution of DS models is typically done in an open-loop manner in combination with standard low level controller, e.g. position con ...

This paper presents a data collection framework and a learning model to understand the motion of an object after being subject to an impulse. The data collection framework consists of an automated dual arm setup hitting an object to each other, like a collaborative air-hockey game. An impact aware extended Kalman filter is proposed for automation of the air-hockey setup which approximates the discontinuous impulse motion equations through a hitting force model by balancing the energies during collision. To

Closed-form solutions are traditionally used in computer vision for estimating rigid body transformations. Here we suggest an iterative solution for estimating rigid body transformations and prove its global convergence. We show that for a number of applic ...

Aude Billard

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Inverse Reinforcement Learning of Pedestrian-Robot Coordination

What is the Teacher's Role in Robot Programming by Demonstration? - Toward Benchmarks for Improved Learning

Combining Dynamical Systems Control and Programming by Demonstration for Teaching Discrete Bimanual Coordination Tasks to a Humanoid Robot

Wearable systems for audio, visual and gaze monitoring

An Origami-Inspired Reconfigurable Suction Gripper for Picking Objects with Variable Shape and Size

Decoding the Grasping Intention from Electromyography during Reaching Motions

Robotic training for hand movements during manual welding with real-time alarm feedback

Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Four-Handed Solo Laparoscopic Anastomosis with the Support of Supernumerary Robotic Arms

Using Reinforcement Learning to Adapt an Imitation Task

EMG-Based Analysis of the Upper Limb Motion

A Dynamical System Approach to Motion and Force Generation in Contact Tasks

Learning Barrier-Certified Polynomial Dynamical Systems for Obstacle Avoidance with Robots

Movement Curvature Planning through Force Field Internal Models

Benchmark for Human-to-Robot Handovers of Unseen Containers with Unknown Filling

Force Adaptation in Contact Tasks with Dynamical Systems

Inferring subjective preferences on robot trajectories using EEG signals

Passive Interaction Control With Dynamical Systems

Learning Inverse Hitting Problem

Iterative Estimation of Rigid-Body Transformations Application to Robust Object Tracking and Iterative Closest Point