基于IAGA的机械手时间最优轨迹规划

为了实现机械手在约束范围内以最快的速度运动，将遗传算法应用于机械手时间最优轨迹规划的研究。在遗传算法进化过程的基础上，提出了一种基于种群集散状态的改进自适应遗传算子，同时采用了优胜劣汰的选择方式，进化后期交换交叉和变异的顺序，有效地解决了简单遗传算法的两大缺陷。对PUMA560的前三铰进行了仿真试验，并与混沌优化法进行了对比分析。实验结果表明，所提出的算法可以有效地防止早熟，收敛速度更快，鲁棒性更好且拥有较强的寻优能力。

Time-optimal trajectory planning for robot manipulators based on improved adaptive genetic algorithm

Aiming at realizing the fastest speed moving of robot manipulators in the constraints, the genetic algorithm was applied in the research of time-optimal trajectory planning of robot manipulators. A scheme of improved self-adaptive genetic algorithm （IAGA） on population species distribution status was proposed based on the course of genetic evolution, the select strategy of suruival of the fittest was adopted, and at the anaphase of evolvement, the order of cross and variation was exchanged, which deals with the two disadvantages of the simple genetic algorithm （SGA） efficiently. Simulations of PUMA560 robot＇s first three joints were carried out. Compared with chaos optimization, the experimental results show that the presented algorithm features virtues of prematurity prevention, faster convergence speed and higher robustness with strong search agility.