【摘要】 为了实现无人挖掘机高效、平稳地完成挖掘任务，本文采用一种改进的Sine混沌映射，对传统非支配排序遗传算法（NSGA-Ⅱ）的初始种群生成做出改进。在同时考虑挖掘机转台、动臂、斗杆和铲斗的运动学约束条件下，选用7次B样条构造挖掘轨迹曲线方程，将最短时间、最小能耗和最小冲击作为优化目标，对挖掘轨迹进行多目标优化。在普通反铲挖掘机上的计算结果表明：改进后的NSGA-Ⅱ算法解集分布更加合理，规划出的挖掘曲线性能更优，可以实现有效的多目标寻优。更多还原

【Abstract】 In order to realize the unmanned excavator to complete the excavation task efficiently and smoothly, this paper adopts an improved Sine chaos mapping to improve the initial population generation of the traditional non-dominated sequential genetic algorithm(NSGA-Ⅱ). Under the kinematic constraints of the excavator turntable, boom, arm and bucket are considered simultaneously, seven times B-splines are chosen to construct the trajectory curve equations, and the shortest time, the smallest energy consumption and the smallest impact are taken as the optimization objectives to optimize the excavation trajectory in a multi-objective manner. The computational results on an ordinary backhoe excavator show that the solution set distribution of the improved NSGA-Ⅱ algorithm is more reasonable, the performance of the planned digging curve is better, and effective multi-objective optimization can be realized.更多还原