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Hybrid dynamic control algorithm for humanoid robots based on reinforcement learning
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DOI：10.1007/s10846-007-9174-5.png)
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In this paper, hybrid integrated dynamic control algorithm for humanoid locomotion mechanism is presented. The proposed structure of controller involves two feedback loops: model-based dynamic controller including impart-force controller and reinforcement learning feedback controller around zero-moment point. The proposed new reinforcement learning algorithm is based on modified version of actor-critic architecture for dynamic reactive compensation. Simulation experiments were carried out in order to validate the proposed control approach.The obtained simulation results served as the basis for a critical evaluation of the controller performance.
Keyword:
humanoid robots
biped locomotion
integrated dynamic control
reinforcement learning
actor-critic method
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2.8
论文数:
3.9K
被引数:
6.9K
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