Path-Integral-Based Reinforcement Learning Algorithm for Goal-Directed Locomotion of Snake-Shaped Robot

Qi Yongqiang, Yang Hailan, Rong Dan, Ke Yi, Lu Dongchen, Li Chunyang, Liu Xiaoting and A. E. Matouk

Discrete Dynamics in Nature and Society, 2021, vol. 2021, 1-12

Abstract: This paper proposes a goal-directed locomotion method for a snake-shaped robot in 3D complex environment based on path-integral reinforcement learning. This method uses a model-free online Q-learning algorithm to evaluate action strategies and optimize decision-making through repeated “exploration-learning-utilization†processes to complete snake-shaped robot goal-directed locomotion in 3D complex environment. The proper locomotion control parameters such as joint angles and screw-drive velocities can be learned by path-integral reinforcement learning, and the learned parameters were successfully transferred to the snake-shaped robot. Simulation results show that the planned path can avoid all obstacles and reach the destination smoothly and swiftly.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:8824377

DOI: 10.1155/2021/8824377

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