81 citations · 284 across the 35 of their papers we have counts for
12 papers · 1 filter
Probabilistic Iterative LQR for Short Time Horizon MPC
Teguh Santoso Lembono, Sylvain Calinon
Optimal control is often used in robotics for planning a trajectory to achieve some desired behavior, as expressed by the cost function. Most works in optimal control focus on find…
Motion Mappings for Continuous Bilateral Teleoperation
Xiao Gao, João Silvério, Emmanuel Pignat +3
Mapping operator motions to a robot is a key problem in teleoperation. Due to differences between workspaces, such as object locations, it is particularly challenging to derive smo…
Generative adversarial training of product of policies for robust and adaptive movement primitives
Emmanuel Pignat, Hakan Girgin, Sylvain Calinon
In learning from demonstrations, many generative models of trajectories make simplifying assumptions of independence. Correctness is sacrificed in the name of tractability and spee…
Learning Constrained Distributions of Robot Configurations with Generative Adversarial Network
Teguh Santoso Lembono, Emmanuel Pignat, Julius Jankowski +1
In high dimensional robotic system, the manifold of the valid configuration space often has a complex shape, especially under constraints such as end-effector orientation or static…
A Laser-based Dual-arm System for Precise Control of Collaborative Robots
João Silvério, Guillaume Clivaz, Sylvain Calinon
Collaborative robots offer increased interaction capabilities at relatively low cost but in contrast to their industrial counterparts they inevitably lack precision. Moreover, in a…
Learning from demonstration using products of experts: applications to manipulation and task prioritization
Emmanuel Pignat, João Silvério, Sylvain Calinon
Probability distributions are key components of many learning from demonstration (LfD) approaches. While the configuration of a manipulator is defined by its joint angles, poses ar…
Active Improvement of Control Policies with Bayesian Gaussian Mixture Model
Hakan Girgin, Emmanuel Pignat, Noémie Jaquier +1
Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a grea…
Analysis and Transfer of Human Movement Manipulability in Industry-like Activities
Noémie Jaquier, Leonel Rozo, Sylvain Calinon
Humans exhibit outstanding learning, planning and adaptation capabilities while performing different types of industrial tasks. Given some knowledge about the task requirements, hu…
Interaction-limited Inverse Reinforcement Learning
Martin Troussard, Emmanuel Pignat, Parameswaran Kamalaruban +2
This paper proposes an inverse reinforcement learning (IRL) framework to accelerate learning when the learner-teacher \textit{interaction} is \textit{limited} during training. Our…
Learning,Generating and Adapting Wave Gestures for Expressive Human-Robot Interaction
Mihalis Panteris, Simon Manschitz, Sylvain Calinon
This study proposes a novel imitation learning approach for the stochastic generation of human-like rhythmic wave gestures and their modulation for effective non-verbal communicati…
Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion
Teguh Santoso Lembono, Carlos Mastalli, Pierre Fernbach +2
In this paper, we propose a framework to build a memory of motion for warm-starting an optimal control solver for the locomotion task of a humanoid robot. We use HPP Loco3D, a vers…
A memory of motion for visual predictive control tasks
Antonio Paolillo, Teguh Santoso Lembono, Sylvain Calinon
This paper addresses the problem of efficiently achieving visual predictive control tasks. To this end, a memory of motion, containing a set of trajectories built off-line, is used…