Safe Table Tennis Swing Stroke with Low-Cost Hardware

Francesco Cursi, Marcus Kalander, Shuang Wu, Xidi Xue, Yu Tian, Guangjian Tian, Xingyue Quan, Jianye Hao

Abstract: Playing table tennis with a human player is a challenging robotic task due to its dynamic nature. Despite a number of researches being devoted to developing robotic table tennis systems, most of the works have demanding hardware requirements and ignore safety measures when generating the swing stoke. To address these issues, we propose a safe motion planning framework that fully pushes the robotic hardware performance limits to play table tennis. In particular, we propose a pipeline to generate manipulator joint trajectories with environmental safety constraints and scale the trajectories to satisfy joint movement limitations. We use three different agents to validate the planning algorithm with our handmade robot platform in both simulation and real-world environments.