Reinforcement learning for freeform robot design
Muhan Li,David Matthews,Sam Kriegman,Muhan Li,David Matthews,Sam Kriegman
Inspired by the necessity of morphological adaptation in animals, a growing body of work has attempted to expand robot training to encompass physical aspects of a robot’s design. However, reinforcement learning methods capable of optimizing the 3D morphology of a robot have been restricted to reorienting or resizing the limbs of a predetermined and static topological genus. Here we show policy gra...
