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 cal...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.展开更多
基金This material is based upon work funded by State Key Laboratory of Robotics and System （HIT） Foundation of China under Grant No. SKLRS-2012-MS-06, China Postdoctoral Science Foundation under Grant No. 2013M531022, Research project of laboratory work in universities of Zhejiang Province under Grant No. ZD201504, Educational technology research program of Zhejiang Province under Grant No. JA027.
文摘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.
