2026
Lifelong Learning-Based MPC for Uncertain Multi-Task Manipulation
RA-L 2026
Modern model-based manipulators are increasingly demanded to perform diverse real-world tasks, e.g. from opening various doors to pick-and-place. Yet as the range of desired tasks grows in the robot's lifetime, model uncertainty increases, which can severely degrade control performance. Adaptive Mod