Additionally, the research will explore full-body contact strategies for complex tasks like dynamic running and manipulating heavy objects. These activities require precise coordination between the arms and legs, demanding reinforcement learning techniques that handle intricate contact events without strict predefined constraints.
Through these advancements, the partnership seeks to push the boundaries of reinforcement learning, enabling the electric Atlas robot to perform more versatile and high-performance tasks in practical applications.