Multi-objective trajectory planning for spraying robot based on hybrid polynomial interpolation and HMONSGA-II

Trajectories of traditional spraying robots are controlled through offline programming, cumbersome, inefficient, and lack accuracy, especially for complex paths. This paper proposes a multi-objective trajectory planning method for a three-axis spraying robot based on hybrid polynomial interpolation and hybrid multi-objective NSGA-II (HMONSGA-II) to address these issues. First, this paper adopts a “7-5-7” hybrid interpolation algorithm to plan the trajectory of the articulated spatial robotic arm, ensuring a continuous and stable spraying trajectory. Second, a multi-constraint objective function is established according to the time-energy-impact performance index. Then, a hybrid multi-objective NSGA-II (HMONSGA-II) optimization algorithm is proposed to optimize the spraying trajectory. Finally, the simulation model is built in Matlab/Simscape to complete the trajectory simulation, and the experimental platform of a three-axis spraying robot is built for validation analysis. The Simulation result shows that compared with the seventh-order polynomial interpolation algorithm, the quintic B-spline interpolation algorithm, the NSGA-II optimization algorithm, and the MOPSO optimization algorithm, the optimal spraying trajectory obtained by the “7-5-7” hybrid interpolation algorithm and the HMONSGA-II optimization algorithm has shorter time, lower energy consumption and more minor impact. The experimental result shows that the maximum deviation between the experiment and simulation is 8.63%, which verifies the proposed algorithm’s effectiveness and the simulation results’ correctness.