Optimization design method for kinematic stability of hexapod robot based on probability-interval hybrid model
Considering the influence of the uncertain parameters of central pattern generator(CPG)model on the kinematic stability of hexapod robot,an optimization design method for the kinematic stability of hexapod robot based on a probability-interval hybrid model was proposed.Firstly,the numerical model of the hexapod robot was established,and the CPG model of the hexapod robot was established based on the Matsuoka and Kimura models.Secondly,the uncertainty variables of the CPG model were described by the probability-interval hybrid model,and the kinematic stability optimization mathematical model of the hexapod robot was also constructed.Then,Karush-Kuhn-Tucker(KKT)optimization condition and the second order fourth moment method based on the maximum entropy principle were used to decouple the kinematic stability optimization design problem of the hexapod robot,and the three-level nested optimization design problem was transformed into a single-level optimization design problem,which realized the efficient solution of the optimization problem.Finally,the kinematic stability approximate model of hexapod robot was established based on radial basis function,and the optimal design solution was obtained by genetic algorithm.The results showed that the proposed method could effectively solve the optimal parameters of the CPG model and improve the kinematic stability of the hexapod robot.Therefore,this method has high application value in the field of robot motion control.
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维普
