基于Tau-jerk策略的机器人运动轨迹规划

Robot Trajectory Planning Based on Tau-jerk Strategy

目的为了提高包装的效率,满足大量包装的需要,设计基于Tau-jerk运动策略的轨迹规划控制六自由度机器人运动的方法。方法首先对Tau-jerk运动策略进行理论分析。然后,通过仿真得出六自由度机器人的速度、加速度曲线光滑连续,加速度的导数也连续,且起点和终点的速度、加速度都为0,并与五次多项式插值法进行对比得到更加平滑的速度、加速度曲线,驱动力矩更小。再以时间优化为目标,采用自适应遗传算法对生成的轨迹进行优化。结果机械臂总的运动时间由原来的12 s缩短到了7.058 s,时间缩短了41.18%,达到了优化效果。结论通过在KUKA Youbot机器人实验平台上进行实验验证,证实该方法可以提高包装效率。

The work aims to design a trajectory planning method based on Tau-jerk motion strategy to control the motion of six-degree-of-freedom robot, so as to improve the efficiency of packaging and meet the needs of mass packaging. First of all, a theoretical analysis on Tau-jerk motion strategy was done. Then, the velocity and acceleration curves of the 6-DOF robot obtained by simulation were smooth and continuous. The derivative of the acceleration was also continuous, and the velocity and acceleration at starting point and ending point were zero. By comparing with the fifth order polynomial interpolation method, the smoother velocity and acceleration curves were obtained and the drive torque was smaller. Taking the time optimization as the goal, the adaptive genetic algorithm was applied to optimize the generated trajectory. The total motion time of the manipulator was reduced from 12 s to 7.058 s, and the time was shortened by 41.18%, which achieved the optimization effect. Validated on the experimental platform of KUKA Youbot robot, the proposed method can improve the packaging efficiency.