Motion Planning and Tracking Control via Basis Function for Swarm Underactuated Robots Based on PSO Algorithm

In this paper, a motion planning and tracking control strategy is proposed for swarm underactuated robots. First, the mathematical model of the swarm underactuated robot is established and the control characteristics are analyzed. To realize the control goal that each underactuated robot reaches the same target state from different initial states, the basis function is used to produce the trajectory of each active link, and the particle swarm optimization (PSO) algorithm is used to optimize the trajectory’s parameters. Then, the sliding mode controller is designed for each active link to track the planned trajectory. Finally, an experimental simulation is used to confirm the effectiveness of the suggested control strategy.