Free gait generation with reinforcement learning for a six-legged robot

Date

2008-03-31

Author

Erden, Mustafa Suphi
Leblebicioğlu, Mehmet Kemal

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper the problem of free gait generation and adaptability with reinforcement learning are addressed for a six-legged robot. Using the developed free gait generation algorithm the robot maintains to generate stable gaits according to the commanded velocity. The reinforcement learning scheme incorporated into the free gait generation makes the robot choose more stable states and develop a continuous walking pattern with a larger average stability margin. While walking in normal conditions with no external effects causing unstability, the robot is guaranteed to have stable walk, and the reinforcement learning only improves the stability. The adaptability of the learning scheme is tested also for the abnormal case of deficiency in one of the rear-legs. The robot gets a negative reinforcement when it falls, and a positive reinforcement when a stable transition is achieved. In this way the robot learns to achieve a continuous pattern of stable walk with five legs. The developed free gait generation with reinforcement learning is applied in real-time on the actual robot both for normal walking with different speeds and learning of five-legged walking in the abnormal case.

Subject Keywords

Control and Systems Engineering, Software, General Mathematics, Computer Science Applications

URI

https://hdl.handle.net/11511/41763

Journal

ROBOTICS AND AUTONOMOUS SYSTEMS

DOI

https://doi.org/10.1016/j.robot.2007.08.001

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

M. S. Erden and M. K. Leblebicioğlu, “Free gait generation with reinforcement learning for a six-legged robot,” ROBOTICS AND AUTONOMOUS SYSTEMS, pp. 199–212, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41763.