针对机器人在特定工作坏境下工作效率低的情况,提出一种以时间为最优的轨迹规划方法。采用七次B样条曲线完成机器人各关节位置-时间序列的插值,并将运动学约束转化为B样条曲线控制顶点的约束,以机器人关节轨迹运行时间最优为优化指标,采用遗传算法对轨迹曲线执行时间最短寻优,规划出满足运动学约束及力矩平滑的时间最优轨迹。实验结果表明,该规划算法能够明显减小加加速度的累积效应,提高机器人执行轨迹的最优时间。 Aiming at the low working efficiency of robots in a specific work environment, a trajectory planning method based on time is proposed. The interpolation of position-time series of robot joints was completed by using seven-times B-spline curve, and the kinematic constraints were transformed into the constraints of vertices controlled by B-spline curves. The optimal operation time of robot joint trajectory was optimized, and genetic algorithm The trajectory curve has the shortest execution time, and the optimal time trajectory that satisfies the kinematic constraints and moment smoothing is planned. Experimental results show that the proposed algorithm can significantly reduce the cumulative effect of jerk and improve the optimal trajectory of robot.