Mobile Robot Control Based on Hybrid Neuro-Fuzzy Value Gradient Reinforcement Learning
This paper uses value gradient learning (VGL) to track a reference trajectory under uncertainties, by computing the optimal left and right torque values for a nonholonomic mobile robot. VGL is a high-performance algorithm in adaptive dynamic programming (ADP). Here, it is used as a critic function after fitting a first-order Sugeno fuzzy neural network (FNN) structure to critic and actor networks. Moreover, this work handles the impacts of unmodeled bounded disturbances with various friction values. The simulation is introduced to compare two approaches. The first uses an actor network that confirms the ability of the mobile robot dynamic model to follow a desired trajectory. This approach demonstrates a significant enhancement of the robot's capability to absorb unstructured disturbance signals and friction effects. The second type of results use a critic-optimal-control approach, calculating the optimal control signal for the affine dynamic model of the robot. This completely removes the actor network to exploit reduced computational complexity with faster responses. The simulation is introduced to compare both cases.
S. Al-Dabooni and D. C. Wunsch, "Mobile Robot Control Based on Hybrid Neuro-Fuzzy Value Gradient Reinforcement Learning," Proceedings of the 2017 International Joint Conference on Neural Networks (2017, Anchorage, AK), pp. 2820-2827, Institute of Electrical and Electronics Engineers (IEEE), May 2017.
The definitive version is available at https://doi.org/10.1109/IJCNN.2017.7966204
2017 International Joint Conference on Neural Networks, IJCNN (2017: May 14-19, Anchorage, AK)
Electrical and Computer Engineering
Intelligent Systems Center
Keywords and Phrases
Dynamic models; Friction; Fuzzy inference; Fuzzy logic; Fuzzy neural networks; Mobile robots; Reinforcement learning; Robot programming; Robots; Adaptive dynamic programming; Bounded disturbances; High performance algorithms; Mobile robot dynamics; Non-holonomic mobile robots; Nonholonomic dynamics; Reference trajectories; Value-gradient learning; Dynamic programming; Nonholonomic dynamic mobile robot
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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01 May 2017