How can robots acquire skills through interactions with the physical world? An interview with Jiaheng Hu

SLAC is a new method that enables robots to learn complex manipulation tasks through real-world reinforcement learning. The approach uses low-fidelity simulations to pretrain a safe, structured latent action space, then performs efficient real-world learning for specific tasks. Tested on a Tiago mobile manipulator, the method Show more