87 citations · 256 across the 24 of their papers we have counts for
28 papers
Infinite-Horizon Value Function Approximation for Model Predictive Control
Armand Jordana, Sébastien Kleff, Arthur Haffemayer +4
Model Predictive Control has emerged as a popular tool for robots to generate complex motions. However, the real-time requirement has limited the use of hard constraints and large…
Parallel and Proximal Constrained Linear-Quadratic Methods for Real-Time Nonlinear MPC
Wilson Jallet, Ewen Dantec, Etienne Arlaud +2
Recent strides in nonlinear model predictive control (NMPC) underscore a dependence on numerical advancements to efficiently and accurately solve large-scale problems. Given the su…
From Compliant to Rigid Contact Simulation: a Unified and Efficient Approach
Justin Carpentier, Louis Montaut, Quentin Le Lidec
Whether rigid or compliant, contact interactions are inherent to robot motions, enabling them to move or manipulate things. Contact interactions result from complex physical phenom…
Vision-based interface for grasping intention detection and grip selection : towards intuitive upper-limb assistive devices
Etienne Moullet, François Bailly, Justin Carpentier +1
Assistive devices for indivuals with upper-limb movement often lack controllability and intuitiveness, in particular for grasping function. In this work, we introduce a novel user…
Risk-Sensitive Extended Kalman Filter
Armand Jordana, Avadesh Meduri, Etienne Arlaud +2
In robotics, designing robust algorithms in the face of estimation uncertainty is a challenging task. Indeed, controllers often do not consider the estimation uncertainty and only…
Contact Models in Robotics: a Comparative Analysis
Quentin Le Lidec, Wilson Jallet, Louis Montaut +3
Physics simulation is ubiquitous in robotics. Whether in model-based approaches (e.g., trajectory optimization), or model-free algorithms (e.g., reinforcement learning), physics si…
MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare
Yann Labbé, Lucas Manuelli, Arsalan Mousavian +7
We introduce MegaPose, a method to estimate the 6D pose of novel objects, that is, objects unseen during training. At inference time, the method only assumes knowledge of (i) a reg…
Constrained Differential Dynamic Programming: A primal-dual augmented Lagrangian approach
Wilson Jallet, Antoine Bambade, Nicolas Mansard +1
Trajectory optimization is an efficient approach for solving optimal control problems for complex robotic systems. It relies on two key components: first the transcription into a s…
ProxNLP: a primal-dual augmented Lagrangian solver for nonlinear programming in Robotics and beyond
Wilson Jallet, Antoine Bambade, Nicolas Mansard +1
Mathematical optimization is the workhorse behind several aspects of modern robotics and control. In these applications, the focus is on constrained optimization, and the ability t…
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…
Stagewise Newton Method for Dynamic Game Control with Imperfect State Observation
Armand Jordana, Bilal Hammoud, Justin Carpentier +1
In this letter, we study dynamic game optimal control with imperfect state observations and introduce an iterative method to find a local Nash equilibrium. The algorithm consists o…
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,…
Leveraging Randomized Smoothing for Optimal Control of Nonsmooth Dynamical Systems
Quentin Le Lidec, Fabian Schramm, Louis Montaut +3
Optimal control (OC) algorithms such as Differential Dynamic Programming (DDP) take advantage of the derivatives of the dynamics to efficiently control physical systems. Yet, in th…
Learning to Manipulate Tools by Aligning Simulation to Video Demonstration
Kateryna Zorina, Justin Carpentier, Josef Sivic +1
A seamless integration of robots into human environments requires robots to learn how to use existing human tools. Current approaches for learning tool manipulation skills mostly r…
Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos
Zongmian Li, Jiri Sedlar, Justin Carpentier +3
In this paper, we introduce a method to automatically reconstruct the 3D motion of a person interacting with an object from a single RGB video. Our method estimates the 3D poses of…
Differentiable Rendering with Perturbed Optimizers
Quentin Le Lidec, Ivan Laptev, Cordelia Schmid +1
Reasoning about 3D scenes from their 2D image projections is one of the core problems in computer vision. Solutions to this inverse and ill-posed problem typically involve a search…
Infinite-Dimensional Sums-of-Squares for Optimal Control
Eloïse Berthier, Justin Carpentier, Alessandro Rudi +1
We introduce an approximation method to solve an optimal control problem via the Lagrange dual of its weak formulation. It is based on a sum-of-squares representation of the Hamilt…
Learning Dynamical Systems from Noisy Sensor Measurements using Multiple Shooting
Armand Jordana, Justin Carpentier, Ludovic Righetti
Modeling dynamical systems plays a crucial role in capturing and understanding complex physical phenomena. When physical models are not sufficiently accurate or hardly describable…
Single-view robot pose and joint angle estimation via render & compare
Yann Labbé, Justin Carpentier, Mathieu Aubry +1
We introduce RoboPose, a method to estimate the joint angles and the 6D camera-to-robot pose of a known articulated robot from a single RGB image. This is an important problem to g…
Exponential Integration for Efficient and Accurate Multi-Body Simulation with Stiff Viscoelastic Contacts
Bilal Hammoud, Luca Olivieri, Ludovic Righetti +2
The simulation of multi-body systems with frictional contacts is a fundamental tool for many fields, such as robotics, computer graphics, and mechanics. Hard frictional contacts ar…
CosyPose: Consistent multi-view multi-object 6D pose estimation
Yann Labbé, Justin Carpentier, Mathieu Aubry +1
We introduce an approach for recovering the 6D pose of multiple known objects in a scene captured by a set of input images with unknown camera viewpoints. First, we present a singl…
Learning Obstacle Representations for Neural Motion Planning
Robin Strudel, Ricardo Garcia, Justin Carpentier +3
Motion planning and obstacle avoidance is a key challenge in robotics applications. While previous work succeeds to provide excellent solutions for known environments, sensor-based…