Publication

A Behavior-Based Mission Planner for Cooperative Autonomous Underwater Vehicles

Publications associées (35)

Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

Robots outside of the fenced factories have to deal with continuously changing environment, this requires fast and flexible modes of control. Planning methods or complex learning models can find optimal paths in complex surroundings, but they are computati ...

EPFL2024

drozBot: Using Ergodic Control to Draw Portraits

Sylvain Calinon

We present drozBot: le robot portraitiste, a robotic system that draws artistic portraits of people. The input images for the portrait are taken interactively by the robot itself. We formulate the problem of drawing portraits as a problem of coverage which ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Hybrid Flock - Formation Control Algorithms

Alcherio Martinoli, Cyrill Silvan Baumann, Jonas Perolini, Emna Tourki

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

2022

Product of experts for robot learning from demonstration

Emmanuel Pignat

Adaptability and ease of programming are key features necessary for a wider spread of robotics in factories and everyday assistance. Learning from demonstration (LfD) is an approach to address this problem. It aims to develop algorithms and interfaces such ...

EPFL2021

Safety Concerns Emerging from Robots Navigating in Crowded Pedestrian Areas

Aude Billard, Diego Felipe Paez Granados, Pericle Salvini

The slogan “robots will pervade our environment” has become a reality. Drones and ground robots are used for commercial purposes while semi-autonomous driving systems are standard accessories to traditional cars. However, while our eyes have been riveted o ...

2021

From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems

Nadia Barbara Figueroa Fernandez

Humans have a remarkable way of learning, adapting and mastering new manipulation tasks. With the current advances in Machine Learning (ML), the promise of having robots with such capabilities seems to be on the cusp of reality. Transferring human-level sk ...

EPFL2019

Learning from demonstration with model-based Gaussian process

Sylvain Calinon, David Ginsbourger, Noémie Laure Gwendoline Jaquier

In learning from demonstrations, it is often desirable to adapt the behavior of the robot in function of the variability retrieved from human demonstrations and the (un)certainty encoded in different parts of the task. In this paper, we propose a novel mul ...

2019

Heterogeneous Target Assignment to Robotic Fiber Positioner Systems

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian

The target assignment methods applied to robotic fiber positioners are only applicable to homogeneous sets of targets to be observed. However, different batches of robotic fiber positioners available at the focal plane of a telescope can be simultaneously ...

IEEE2019

Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance

Sylvain Calinon, Emmanuel Pignat

For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that requires expert knowledge. An alterna ...

2018

Joining high-level symbolic planning with low-level motion primitives in adaptive HRI: application to dressing assistance

Sylvain Calinon, Emmanuel Pignat

Idiap2018

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