Abstract: To solve the problem of trajectory planning for industrial robots with shortest running time,a double population genetic andchaotic optimization algorithm was proposed.By taking the sum of time intervals between any two nodes as the optimization objective,the angular velocity,angular acceleration and angular acceleration of each joint as theconstraint condition,the trajectory of the robot was simulated,which used five polynomial to fit the joint space nodes.Based on the strong local search ability of chaotic algorithm and the fast evolution speed of double population genetic algorithm,the robotic trajectory planning was given to obtain the optimal time trajectory.Through a case study of 3 degree of freedom manipulator,the proposed algorithm was proved to smooth the trajectory of robot's end effector and made time optimum,which could prolong the service life and improve the production efficiency.

Key words: double population genetic algorithm, chaos search algorithm, optimal time, trajectory planning, robot

摘要： 针对以最短运行时间为目标的工业机器人轨迹规划问题,提出一种基于混沌局部搜索的双种群遗传最优时间轨迹规划算法。首先以各个节点之间的时间间隔之和为优化目标,以各关节的角速度、角加速度和角加加速度为约束条件,利用五次多项式拟合规划的关节空间位置节点模拟机器人的运行轨迹;然后,利用双种群遗传算法全局搜索能力强、进化速度快和混沌算法局部搜索能力强的优点,提出一种基于双种群遗传混沌优化算法的机器人轨迹规划方法,规划最优时间轨迹;最后,以3自由度空间机械臂为例,验证了所提算法能够使机器人末端执行器的运行轨迹平滑且时间最优。该算法应用于机器人轨迹规划可以延长机器人使用寿命,提高生产效率。

关键词: 双种群遗传算法, 混沌搜索算法, 最优时间, 轨迹规划, 机器人