Research on Gait Trajectory Planning of Wall-Climbing Robot Based on Improved PSO Algorithm

Abstract

In order to reduce the labor intensity of high-altitude workers and realize the cleaning and maintenance of high-rise building exteriors, this paper proposes a design for a 4-DOF bipedal wall-climbing bionic robot inspired by the inchworm’s movement. The robot utilizes vacuum adsorption for vertical wall attachment and legged movement for locomotion. To enhance the robot’s movement efficiency and reduce wear on the adsorption device, a gait mimicking an inchworm’s movement is planned, and foot trajectory planning is performed using a quintic polynomial function. Under velocity constraints, foot trajectory optimization is achieved using an improved Particle Swarm Optimization (PSO) algorithm, determining the quintic polynomial function with the best fitness through simulation. Finally, through comparative experiments, the climbing time of the robot closely matches the simulation results, validating the trajectory planning method’s accuracy.