21 citations · 21 across the 1 of their papers we have counts for
2 papers
cs.RO2021★ 21 cited
Optimal Stroke Learning with Policy Gradient Approach for Robotic Table Tennis
Yapeng Gao, Jonas Tebbe, Andreas Zell
Learning to play table tennis is a challenging task for robots, as a wide variety of strokes required. Recent advances have shown that deep Reinforcement Learning (RL) is able to s…
cs.RO2020
Sample-efficient Reinforcement Learning in Robotic Table Tennis
Jonas Tebbe, Lukas Krauch, Yapeng Gao +1
Reinforcement learning (RL) has achieved some impressive recent successes in various computer games and simulations. Most of these successes are based on having large numbers of ep…