Simulation Trains Robot Tennis Player
arXiv | Google DeepMind has developed a robot that plays table tennis at an amateur human level. Combining simulation and real-world data, the robot achieved a 45% match win rate against varied skill levels. The system’s capabilities were refined through iterative training cycles, leveraging simulation for efficiency and accuracy in skill acquisition and real-time adaptation to opponents.
Read More – https://arxiv.org/html/2408.03906v1
Image – arXiv:2408.03906
