A novel Q-Learning Based Cartesian Model Reference Compliance Controller Implementation for a Humanoid Robotic Arm

SG Khan, G Herrmann, F.L Lewis, AG Pipe, CR Melhuish

    Research output: Other contributionpeer-review

    Abstract

    This paper presents the implementation (real time and simulation) of a model-free Q-learning based discrete model reference compliance controller for a humanoid robot arm. The Reinforcement learning (RL) scheme uses a recently developed Q-learning scheme to develop an optimal policy on-line. The RL Cartesian (x and y) tracking controller with model reference compliance was implemented using two links (shoulder flexion and elbow flexion joints) of the right arm of the humanoid Bristol-Elumotion-Robotic-Torso II (BERT II) torso.
    Original languageEnglish
    Number of pages6
    DOIs
    Publication statusPublished - 2011

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