Google DeepMinds Table Tennis Robot Competes at Human-Level AIM [Video]

Researchers from Google DeepMind have developed a robot capable of playing table tennis at an amateur human level. This robotic system, featuring a 6 DoF ABB 1100 arm mounted on linear gantries, has been tested against human players of varying skill levels, winning 45% of the matches overall. 

The robot’s design utilises a hierarchical and modular policy architecture, which includes low-level controllers for specific skills and a high-level controller for decision-making based on match statistics.

The robot employs advanced techniques to bridge the simulation-to-real-world gap, enabling it to adapt to unseen opponents and improve its decision-making process. It uses a combination of reinforcement learning and imitation learning to train its skills in simulation before deploying them in real-world matches. The system’s adaptability and strategic capabilities are enhanced by …