APPLR: Adaptive Planner Parameter Learning from Reinforcement
Zifan Xu,Gauraang Dhamankar,Anirudh Nair,Xuesu Xiao,Garrett Warnell,Bo Liu,Zizhao Wang,Peter Stone,Zifan Xu,Gauraang Dhamankar,Anirudh Nair,Xuesu Xiao,Garrett Warnell,Bo Liu,Zizhao Wang,Peter Stone
Classical navigation systems typically operate using a fixed set of hand-picked parameters (e.g. maximum speed, sampling rate, inflation radius, etc.) and require heavy expert re-tuning in order to work in new environments. To mitigate this requirement, it has been proposed to learn parameters for different contexts in a new environment using human demonstrations collected via teleoperation. Howev...
