Slipping and Tripping Reflexes for Bipedal Robots
Autonomous Robots
Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators
Fuzzy Sets and Systems - Special issue: Fuzzy set techniques for intelligent robotic systems
Journal of Intelligent and Robotic Systems
T-S model based indirect adaptive fuzzy control using online parameter estimation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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As an assistant tool for human beings, humanoid robot is expected to cooperate with people to do certain jobs. Therefore, it must have high intelligence to adapt to common working condition. The objective of this paper is to propose an adaptive fuzzy logic control (FLC) method to improve system adaptability and stability, which can adjust hip and ankle joint based on sensor information. Furthermore, it can real time adjust controller parameters to improve FLC performance. Based on sensor information, humanoid robot can get environment and inherent situation and use the adaptive-FLC to realize stable locomotion. The effectiveness of the proposed method is shown with simulations based on the parameters of the “IHR-1” humanoid robot.