Preprint Open access
Potential-Field Action Representation for Reinforcement Learning in Contact-Rich Manipulation
Model-free reinforcement learning can acquire contact-rich robotic manipulation skills through trial-and-error interaction, but it often requires the policy to learn both task strategy and low-level motion generation. In this setting, the action representation is critical because it determines how policy outputs are co …