基于改进量子遗传算法的机器人关节轨迹优化

电子元器件体积较小，对它进行分拣较一般分拣工作困难且工作量巨大，应用机器人分拣可大大提高工作效率。采用七次多项式曲线插值的方法进行轨迹规划，使运动关节的角速度、角加速度和角急动度曲线光滑连续；提出一种改进的量子遗传算法，引入正态分布概率密度函数以改进量子门旋转角步长策略，对关节运动轨迹进行最短时间优化，使机器人能够在满足非线性约束条件的基础上具有最优关节轨迹曲线。仿真结果表明：该轨迹算法能够快速有效地缩短机械臂关节运动时间。

Joint Trajectory Optimization of Robot Based on Improved Quantum Genetic Algorithm

The electronic components are small in size, so their sorting is more difficult than regular sorting, and the workload is heavy, the application of robot sorting can greatly improve the work efficiency. Interpolation method of seventh degree polynomial curve was used for trajectory planning to make the angular velocity, angular acceleration and angular jerk curves of the motion joints smooth and continuous; an improved quantum genetic algorithm was proposed, in which the normal distribution probability density function was introduced to improve the quantum gate rotation angle step strategy and to optimize the joint motion trajectory in the shortest time, so the robot could obtain the optimal joint trajectory curve on the basis of meeting the nonlinear constraints. The simulation results show that the trajectory algorithm can shorten the movement time of the robotic arm joints quickly and efficiently.