3 papers
cs.RO2026
Infeasible optimization problems and the hierarchical augmented Lagrangian method in imitation learning
Roland Andrews, Justin Carpentier, Ajay Sathya
Imitation learning (IL) is an effective approach to train complex robotics policies. Recent works have introduced hard constraints into imitation-learning optimization problems to…
cs.RO2026
CACTO-SL: Using Sobolev Learning to improve Continuous Actor-Critic with Trajectory Optimization
Elisa Alboni, Gianluigi Grandesso, Gastone Pietro Rosati Papini +2
Trajectory Optimization (TO) and Reinforcement Learning (RL) are powerful and complementary tools to solve optimal control problems. On the one hand, TO can efficiently compute loc…
cs.RO2025
On the Conic Complementarity of Planar Contacts
Yann de Mont-Marin, Louis Montaut, Jean Ponce +2
We present a unifying theoretical result that connects two foundational principles in robotics: the Signorini law for point contacts, which underpins many simulation methods for pr…