2026
Accelerated co-design of robots through morphological pretraining
ICLR 2026poster
The co-design of robot morphology and neural control typically requires using reinforcement learning to approximate a unique control policy gradient for each body plan, demanding massive amounts of training data to measure the performance of each design. Here we show that a universal, morphology-agn…