Research on End Attitude Optimization of Hybrid Robot Based on Improved NSGA-III Algorithm

Due to the advantages of serial and parallel robots, the hybrid robot has been applied to the milling of complex surfaces. The attitude optimization of the end of the robot is a key step in the machining process. However, the traditional attitude optimization method only focuses on the interaction between the tool shaft and the part, and does not consider the influence of the motion of the driving joint on the actual machining. In this regard, based on the kinematic constraints of the 5-DOF hybrid robot, this paper constructs multi-objective objective functions with robot running time, energy consumption and impact as indicators, proposes an improved third-generation non-dominated sorting genetic algorithm, and introduces population initialization based on Logistic-Tent chaotic mapping and Levy flight strategy. And the Pareto solution set satisfying the constraints is calculated, and the relative optimal solution in the Pareto front is taken as the attitude optimization result. And several sets of vibration related experiments are designed in this paper. The results show that compared with traditional methods, the proposed attitude optimization method can obtain better joint trajectory smoothness and terminal stationarity, and also has higher robot operation efficiency.