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Path-Integral-Based Reinforcement Learning Algorithm for Goal-Directed Locomotion of Snake-Shaped Robot.
- Source :
-
Discrete Dynamics in Nature & Society . 2/8/2021, p1-12. 12p. - Publication Year :
- 2021
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10260226
- Database :
- Academic Search Index
- Journal :
- Discrete Dynamics in Nature & Society
- Publication Type :
- Academic Journal
- Accession number :
- 148567404
- Full Text :
- https://doi.org/10.1155/2021/8824377