基于改进NURBS曲线插补算法的食品分拣机器人轨迹规划

目的：为了更好地规划食品分拣机器人的运动轨迹，降低其振动幅度，使食品分拣机器人能够高精度地完成任务。方法：以Delta并联机器人为基础，结合NURBS曲线插补算法和改进的遗传算法，提出了一种以最优运动时间为目标的食品分拣机器人路径规划方法。采用改进遗传算法来优化NURBS曲线。通过仿真对优化前后进行对比分析，验证了该优化方法的可行性。结果：与优化前相比，所提的优化方法可以在一定程度上降低食品分拣机器人的运动时间，从优化前的3 230 ms降低到优化后的3 070 ms。关节空间的机器人曲线也更加平滑，可以充分发挥并联机器人的性能。结论：该轨迹规划方法能有效提高食品分拣机器人的分拣稳定性和效率。

Trajectory planning method of food sorting robot based on improved NURBS curve interpolation algorithm

Objective:In order to better plan the motion trajectory of the food sorting robot, reduce its vibration amplitude, and enable the food sorting robot to complete the task with high precision.Methods:Based on the delta parallel robot, combined with NURBS curve interpolation algorithm and improved genetic algorithm, a path planning method of food sorting robot aiming at the optimal motion time was proposed. The NURBS curve was optimized by improved genetic algorithm. The feasibility of the optimization method was verified by the comparative analysis before and after optimization through simulation.Results:Compared with before optimization, the proposed optimization method can reduce the motion time of food sorting robot to a certain extent, from 3 230 ms before optimization to 3 070 ms after optimization. The robot curve in joint space was also smoother, which can give full play to the performance of parallel robot.Conclusion:The trajectory planning method can effectively improve the sorting stability and efficiency of food sorting robot.