8 citations · 16 across the 8 of their papers we have counts for
4 papers · 1 filter
Differentiable Collision Detection: a Randomized Smoothing Approach
Louis Montaut, Quentin Le Lidec, Antoine Bambade +3
Collision detection appears as a canonical operation in a large range of robotics applications from robot control to simulation, including motion planning and estimation. While the…
Enforcing the consensus between Trajectory Optimization and Policy Learning for precise robot control
Quentin Le Lidec, Wilson Jallet, Ivan Laptev +2
Reinforcement learning (RL) and trajectory optimization (TO) present strong complementary advantages. On one hand, RL approaches are able to learn global control policies directly…
Augmenting differentiable physics with randomized smoothing
Quentin Le Lidec, Louis Montaut, Cordelia Schmid +2
In the past few years, following the differentiable programming paradigm, there has been a growing interest in computing the gradient information of physical processes (e.g., physi…
Collision Detection Accelerated: An Optimization Perspective
Louis Montaut, Quentin Le Lidec, Vladimir Petrik +2
Collision detection between two convex shapes is an essential feature of any physics engine or robot motion planner. It has often been tackled as a computational geometry problem,…