81 citations · 284 across the 35 of their papers we have counts for
9 papers · 1 filter
Learning from demonstration with model-based Gaussian process
Noémie Jaquier, David Ginsbourger, Sylvain Calinon
In learning from demonstrations, it is often desirable to adapt the behavior of the robot as a function of the variability retrieved from human demonstrations and the (un)certainty…
Bayesian Optimization Meets Riemannian Manifolds in Robot Learning
Noémie Jaquier, Leonel Rozo, Sylvain Calinon +1
Bayesian optimization (BO) recently became popular in robotics to optimize control parameters and parametric policies in direct reinforcement learning due to its data efficiency an…
Gaussians on Riemannian Manifolds: Applications for Robot Learning and Adaptive Control
Sylvain Calinon
This article presents an overview of robot learning and adaptive control applications that can benefit from a joint use of Riemannian geometry and probabilistic representations. Th…
Memory of Motion for Warm-starting Trajectory Optimization
Teguh Santoso Lembono, Antonio Paolillo, Emmanuel Pignat +1
Trajectory optimization for motion planning requires good initial guesses to obtain good performance. In our proposed approach, we build a memory of motion based on a database of r…
Nullspace Structure in Model Predictive Control
Hakan Girgin, Sylvain Calinon
Robotic tasks can be accomplished by exploiting different forms of redundancies. This work focuses on planning redundancy within Model Predictive Control (MPC) in which several pat…
Variational Inference with Mixture Model Approximation: Robotic Applications
Emmanuel Pignat, Teguh Lembono, Sylvain Calinon
We propose a method to approximate the distribution of robot configurations satisfying multiple objectives. Our approach uses variational inference, a popular method in Bayesian co…
Bayesian Gaussian mixture model for robotic policy imitation
Emmanuel Pignat, Sylvain Calinon
A common approach to learn robotic skills is to imitate a demonstrated policy. Due to the compounding of small errors and perturbations, this approach may let the robot leave the s…
Improving dual-arm assembly by master-slave compliance
Markku Suomalainen, Sylvain Calinon, Emmanuel Pignat +1
In this paper we show how different choices regarding compliance affect a dual-arm assembly task. In addition, we present how the compliance parameters can be learned from a human…
Tensor-variate Mixture of Experts for Proportional Myographic Control of a Robotic Hand
Noémie Jaquier, Robert Haschke, Sylvain Calinon
When data are organized in matrices or arrays of higher dimensions (tensors), classical regression methods first transform these data into vectors, therefore ignoring the underlyin…