Reinforcement learning for path planning of free-floating space robotic manipulator with collision avoidance and observation noise
Ahmad Al Ali,
Zheng H. Zhu
Abstract:This study introduces a novel approach for the path planning of a 6-degree-of-freedom free-floating space robotic manipulator, focusing on collision and obstacle avoidance through reinforcement learning. It addresses the challenges of dynamic coupling between the spacecraft and the robotic manipulator, which significantly affects control and precision in the space environment. An innovative reward function is introduced in the reinforcement learning framework to ensure accurate alignment of the manipulator’s e… Show more
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