Abstract
According to the features of movements of humanoid robot, a control system for humanoid robot walking on uneven terrain is present. Constraints of stepping over stairs are analyzed and the trajectories of feet are calculated by intelligent computing methods. To overcome the shortcomings resulted from directly controlling the robot by neural network (NN) and fuzzy logic controller (FLC), a revised particle swarm optimization (PSO) algorithm is proposed to train the weights of NN and rules of FLC. Simulations and experiments on different control methods are achieved for a detailed comparison. The results show that using the proposed methods can obtain better control effect.
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