211 citations · 567 across the 48 of their papers we have counts for
5 papers · 1 filter
Robust Visual Sim-to-Real Transfer for Robotic Manipulation
Ricardo Garcia, Robin Strudel, Shizhe Chen +3
Learning visuomotor policies in simulation is much safer and cheaper than in the real world. However, due to discrepancies between the simulated and real data, simulator-trained po…
Learning Video-Conditioned Policies for Unseen Manipulation Tasks
Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev
The ability to specify robot commands by a non-expert user is critical for building generalist agents capable of solving a large variety of tasks. One convenient way to specify the…
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…
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…
Learning visual policies for building 3D shape categories
Alexander Pashevich, Igor Kalevatykh, Ivan Laptev +1
Manipulation and assembly tasks require non-trivial planning of actions depending on the environment and the final goal. Previous work in this domain often assembles particular ins…