2025
Adaptive Contact-Rich Manipulation Through Few-Shot Imitation Learning With Force-Torque Feedback and Pre-Trained Object Representations
RA-L 2025
Imitation learning offers a pathway for robots to perform repetitive tasks, allowing humans to focus on more engaging and meaningful activities. However, challenges arise from the need for extensive demonstrations and the disparity between training and real-world environments. This paper focuses on