How to Peel with a Knife: Aligning Fine-Grained Manipulation with Human Preference

Researchers developed a two-stage learning framework enabling robots to perform complex manipulation tasks like food peeling with over 90% success rates. The system combines force-aware imitation learning with human preference-based refinement, achieving strong generalization across different produce types using only 50-200 training examples.