RoHIL: Robust Human-in-the-Loop Robotic Reinforcement Learning Against Illumination Variations

Shuoqin Zhang, Yixin Xiong, Xiru Gao +4

Human-in-the-loop reinforcement learning systems achieve near-perfect success on the workstation where they are trained, but collapse when the same robot is moved to a workstation…