基于改进麻雀搜索算法的机器人能耗最优轨迹规划

Robot Trajectory Planning Method with Optimal Energy Consumption Based on Improved SparrowSearch Algorithm

为提高机器人能量利用率,提出一种基于改进麻雀搜索算法的机器人能耗最优轨迹规划方法。为使机器人各关节速度、加速度、加加速度有界连续,采用7次B样条曲线构造关节空间轨迹。将运动学参数与动力学参数相结合计算机器人工作总能耗。在麻雀搜索算法基础上,用精英反向学习、非支配排序以及高斯-柯西变异策略对其进行改进求解出最优能耗所对应的时间序列,进而规划出能耗最优连续运动轨迹。仿真结果表明,所提轨迹规划方法不仅能实现轨迹的连续平滑,而且能有效降低能量消耗,节约生产成本。

In order to improve the energy availability of robots,an optimal trajectory planning method for energy consumption of the robot based on an improved sparrow search algorithm is proposed.To make the velocity,acceleration,and jerk of the robot bounded and continuous,the 7th B-spline is applied to joint space trajectory planning.The kinematics parameters and dynamics parameters are combined to calculate the total energy consumption of the robot.The sparrow search algorithm is improved by elite reverse learning,non-dominant sorting and,Gauss-Cauchy variation strategies to get the time series corresponding to the optimal energy consumption,so as to plan the optimal continuous trajectory.Simulation results show that the proposed trajectory planning method can not only smooth the trajectory but also can effectively reduce energy consumption and save production costs.