改进NSGA-Ⅱ算法的机械臂多目标轨迹优化OA

In response to the limitations of the traditional non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ algorithm),which tends to get stuck in local optimal and has slow convergence when applied to trajectory optimization with multiple objectives such as time optimization,low energy consumption,and minimal pulsation impact,an enhanced multi-objective optimization algorithm is proposed.The present approach involves the optimal point set for optimizing initial population generation in multi-objective problems,introducing a DC operator and multiple evolutionary strategies,and implementing population optimization strategies to enhance the generation of new populations.An improved SDE-NSGA-Ⅱ algorithm of multi-objective trajectory optimization of manipulator was developed and its performance was simulated.Finally,the algorithm was validated on the JAKA Zu3 robot arm.The results demonstrate that the enhanced algorithm provides a more evenly distributed Pareto optimal solution set and shorter iteration times.Additionally,a 7th-order B-spline curve interpolation method can be utilized to construct a continuous smooth trajectory of joint velocity,acceleration,and jerk in order to ensure effective manipulator operation.