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Aude Billard

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Publications associées (263)

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

Aude Billard, Nadia Barbara Figueroa Fernandez, Mikhail Koptev

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 ...

2021

Crowd against the machine: A simulation-based benchmark tool to evaluate and compare robot capabilities to navigate a human crowd

Aude Billard, David Julian Gonon, Diego Felipe Paez Granados

The evaluation of robot capabilities to navigate human crowds is essential to conceive new robots intended to operate in public spaces. This paper initiates the development of a benchmark tool to evaluate such capabilities; our long term vision is to provi ...

IEEE2021

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

Aude Billard, Rui Wu

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 ...

2021

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Aude Billard, Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, Iason Batzianoulis, Fumiaki Iwane

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI ...

NATURE PORTFOLIO2021

Multimodal Sensory Learning for Real-time, Adaptive Manipulation

Aude Billard, Ahalya Prabhakar

Adaptive control for real-time manipulation requires quick estimation and prediction of object properties. While robot learning in this area primarily focuses on using vision, many tasks cannot rely on vision due to object occlusion. Here, we formulate a l ...

2021

Reactive Navigation in Crowds for Non-holonomic Robots with Convex Bounding Shape

Aude Billard, David Julian Gonon, Diego Felipe Paez Granados

This paper describes a novel method for non-holonomic robots of convex shape to avoid imminent collisions with moving obstacles. The method's purpose is to assist navigation in crowds by correcting steering from the robot's path planner or driver. We evalu ...

2021

Hand-Object Interaction: From Human Demonstrations to Robot Manipulation

Aude Billard

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 ...

FRONTIERS MEDIA SA2021

Foot Control of a Surgical Laparoscopic Gripper via 5DoF Haptic Robotic Platform: Design, Dynamics and Haptic Shared Control

Mohamed Bouri, Aude Billard, Walid Amanhoud, Jacob Hernandez Sanchez

Foot devices have been ubiquitously used in surgery to control surgical equipment. Most common applications are foot switches for electro-surgery, endoscope positioning and tele-robotic consoles. Switches fall short of providing continuous control as requi ...

2021

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

Aude Billard, Walid Amanhoud, Farshad Khadivar, Sthithpragya Gupta

The inverse dynamics of a robotic manipulator is instrumental in precise robot control and manipulation. However, acquiring such a model is challenging, not only due to unmodelled non-linearities such as joint friction, but also from a machine learning per ...

IEEE2021

Learning to Hit: A statistical Dynamical System based approach

Aude Billard, Michael Bosongo Bombile, Harshit Khurana

This paper proposes a manipulation scheme based on learning the motion of objects after being hit by a robotic end-effector. This allows for the object to be positioned at a desired location outside the physical workspace of the robot. An estimate of the o ...

IEEE2021

Hand pose selection in a bimanual fine-manipulation task

Aude Billard, Kunpeng Yao

Many daily tasks involve the collaboration of both hands. Humans dexterously adjust hand poses and modulate the forces exerted by fingers in response to task demands. Hand pose selection has been intensively studied in unimanual tasks, but little work has ...

2021

Credit Assignment Safety Learning from Human Demonstrations

Aude Billard, Ahalya Prabhakar

A critical need in assistive robotics, such as assistive wheelchairs for navigation, is a need to learn task intent and safety guarantees through user interactions in order to ensure safe task performance. For tasks where the objectives from the user are n ...

2021

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues

Aude Billard, José Santos-Victor, Konstantinos Chatzilygeroudis, Nuno Ricardo Ferreira Duarte

Humans manage to communicate action intentions in a non-verbal way, through body posture and movement. We start from this observation to investigate how a robot can decode a human's non-verbal cues during the manipulation of an object, with specific physic ...

IEEE2020

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

Pascal Frossard, Aude Billard, Andrea Cavallaro, Konstantinos Chatzilygeroudis, Nuno Ricardo Ferreira Duarte, Apostolos Modas

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 ...

2020

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

Aude Billard, Sophie Marie Marthe Wurth, Marion Aimée Geneviève Badi-Dubois, Silvestro Micera, Marco Capogrosso, Seyed Sina Mirrazavi Salehian, Sara Conti

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 ...

IOP PUBLISHING LTD2020

Force Adaptation in Contact Tasks with Dynamical Systems

Aude Billard, Walid Amanhoud, Mahdi Khoramshahi

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 ...

IEEE2020

Benchmark for Bimanual Robotic Manipulation of Semi-deformable Objects

Aude Billard, Konstantinos Chatzilygeroudis, Ilaria Lauzana, Kunpeng Yao, Bernardo Fichera, Farshad Khadivar, Fanjun Bu

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. ...

2020

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

Aude Billard, Kunpeng Yao

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 ...

2020

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

Aude Billard, Mahdi Khoramshahi, Seyed Sina Mirrazavi Salehian, Aileen Charlotte Naef, Karl Gustav Henriks

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 ...

IEEE2020

Intent Prediction Based on Biomechanical Coordination of EMG and Vision-Filtered Gaze for End-Point Control of an Arm Prosthesis

Aude Billard, Silvestro Micera, Iason Batzianoulis, Nili Eliana Krausz

We propose a novel controller for powered prosthetic arms, where fused EMG and gaze data predict the desired end-point for a full arm prosthesis, which could drive the forward motion of individual joints. We recorded EMG, gaze, and motion-tracking during p ...

2020

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