7 papers
Coupled Local and Global World Models for Efficient First Order RL
Joseph Amigo, Rooholla Khorrambakht, Nicolas Mansard +1
World models offer a promising avenue for more faithfully capturing complex dynamics, including contacts and non-rigidity, as well as complex sensory information, such as visual pe…
Direct Dynamic Retargeting for Humanoid Imitation Learning from Videos
Constant Roux, Ludovic De Matteïs, Armand Jordana +4
Imitation Learning from monocular video demonstrations provides a scalable approach for teaching complex skills to humanoid robots. However, translating human motion to humanoids r…
Learning-Guided Force-Feedback Model Predictive Control with Obstacle Avoidance for Robotic Deburring
Krzysztof Wojciechowski, Ege Gursoy, Arthur Haffemayer +4
Model Predictive Control (MPC) is widely used for torque-controlled robots, but classical formulations often neglect real-time force feedback and struggle with contact-rich industr…
Warm-Starting Collision-Free Model Predictive Control With Object-Centric Diffusion
Arthur Haffemayer, Alexandre Chapin, Armand Jordana +4
Acting in cluttered environments requires predicting and avoiding collisions while still achieving precise control. Conventional optimization-based controllers can enforce physical…
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…
Multi-step manipulation task and motion planning guided by video demonstration
Kateryna Zorina, David Kovar, Mederic Fourmy +5
This work aims to leverage instructional video to solve complex multi-step task-and-motion planning tasks in robotics. Towards this goal, we propose an extension of the well-establ…