Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions
Desong Du,Shaohang Han,Naiming Qi,Haitham Bou Ammar,Jun Wang,Wei Pan,Desong Du,Shaohang Han,Naiming Qi,Haitham Bou Ammar,Jun Wang,Wei Pan
Reinforcement learning (RL) exhibits impressive performance when managing complicated control tasks for robots. However, its wide application to physical robots is limited by the absence of strong safety guarantees. To overcome this challenge, this paper explores the control Lyapunov barrier function (CLBF) to analyze the safety and reachability solely based on data without explicitly employing a ...
