Search Results for author:
Found 15 papers, 9 papers with code
CACTO-SL: Using Sobolev Learning to improve Continuous Actor-Critic with Trajectory Optimization
Recently, we have proposed CACTO (Continuous Actor-Critic with Trajectory Optimization), an algorithm that uses TO to guide the exploration of an actor-critic RL algorithm.
Vision-based interface for grasping intention detection and grip selection : towards intuitive upper-limb assistive devices
Assistive devices for indivuals with upper-limb movement often lack controllability and intuitiveness, in particular for grasping function.
MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare
Second, we introduce a novel approach for coarse pose estimation which leverages a network trained to classify whether the pose error between a synthetic rendering and an observed image of the same object can be corrected by the refiner.
Enforcing the consensus between Trajectory Optimization and Policy Learning for precise robot control
Reinforcement learning (RL) and trajectory optimization (TO) present strong complementary advantages.
Online Learning and Control of Complex Dynamical Systems from Sensory Input
Identifying an effective model of a dynamical system from sensory data and using it for future state prediction and control is challenging.
Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos
First, we introduce an approach to jointly estimate the motion and the actuation forces of the person on the manipulated object by modeling contacts and the dynamics of the interactions.
Differentiable Rendering with Perturbed Optimizers
Notably, images depend both on the properties of observed scenes and on the process of image formation.
Learning Dynamical Systems from Noisy Sensor Measurements using Multiple Shooting
In this work, we introduce a generic and scalable method based on multiple shooting to learn latent representations of indirectly observed dynamical systems.
Single-view robot pose and joint angle estimation via render & compare
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.
Ranked #3 on
Robot Pose Estimation
on DREAM-dataset
Learning Obstacle Representations for Neural Motion Planning
Motion planning and obstacle avoidance is a key challenge in robotics applications.
Robotics
CosyPose: Consistent multi-view multi-object 6D pose estimation
Second, we develop a robust method for matching individual 6D object pose hypotheses across different input images in order to jointly estimate camera viewpoints and 6D poses of all objects in a single consistent scene.
Crocoddyl: An Efficient and Versatile Framework for Multi-Contact Optimal Control
Additionally, we propose a novel optimal control algorithm called Feasibility-driven Differential Dynamic Programming (FDDP).
Robotics Optimization and Control
Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planning
We address the problem of visually guided rearrangement planning with many movable objects, i. e., finding a sequence of actions to move a set of objects from an initial arrangement to a desired one, while relying on visual inputs coming from an RGB camera.
Differential Dynamic Programming for Multi-Phase Rigid Contact Dynamics
A common strategy today to generate efficient locomotion movements is to split the problem into two consecutive steps: the first one generates the contact sequence together with the centroidal trajectory, while the second one computes the whole-body trajectory that follows the centroidal pattern.
Estimating 3D Motion and Forces of Person-Object Interactions from Monocular Video
First, we introduce an approach to jointly estimate the motion and the actuation forces of the person on the manipulated object by modeling contacts and the dynamics of their interactions.
