Yvan R. Pétillot

Path Planning for Manipulation Using Experience-Driven Random Trees

Robotic systems may frequently come across similar manipulation planning problems that result in similar motion plans. Instead of planning each problem from scratch, it is preferable to leverage previously computed motion plans, i.e., experiences, to ease the planning. Different approaches have been