Foot Trajectory Optimization of the Chebyshev Wheel-legged Robot Based on Quantum Particle Swarm Optimization

To obtain the optimal foot trajectory of the Chebyshev wheel-legged robot and improve its moving speed and obstacle-crossing ability, a method of foot trajectory optimization of the Chebyshev linkage mechanism based on a quantum particle swarm optimization algorithm was proposed. The motion process of the Chebyshev linkage mechanism is analyzed, and the displacement equation of the foot is derived by geometric relation. The design parameters are determined, the objective function of foot trajectory optimization is constructed, the constraint conditions are set, and the optimization coefficient is introduced to adapt to different actual optimization requirements. The elementary particle swarm optimization algorithm and quantum particle swarm optimization algorithm were used to solve the problem, the foot trajectory was drawn through calculation, and the motion performance of the wheel-legged robot was simulated and verified by simulation software. The results show that the quantum particle swarm optimization algorithm has fast convergence speed, strong optimization ability, high solving efficiency, and stronger applicability. The research results can provide a reference scheme for the dimensional design of the Chebyshev wheel-legged robot walking mechanism.