基于平滑反射运动的工业机器人多变量时间最优轨迹规划研究

Research on multivariable time optimal trajectory planning of industrial robot based on smooth reflection motion

针对如何提升高精度装配工业机器人工作效率的问题,设计了一种基于平滑反射运动的工业机器人多变量时间最优轨迹规划方法,该方法可有效适用于健康和退化状态。研究了工业关节型机器人的运动链,并根据精确装配任务的要求和机械人各关节的性能,采用了新颖的多变量优化方法,将任意特定路径的执行时间缩到最短;采用异步方式调整了加速时间,实现了执行效率的优化;在光电子行业的模块化6自由度(DoF)机器人上进行了具体测试。实验结果表明:相比于其他最优执行运动规划方法,该方法将机器人执行轨迹的速度提高39%,即使在退化关节模式下仍具有较好的优化性能。

Aiming at the problem of how to improve the work efficiency of high-precision assembly industrial robots,a multivariable time-optimal trajectory planning method for industrial robots based on smooth reflection motion was designed,which can be effectively applied to health and degraded states.The kinematic chain of the industrial articulated robot was studied,and according to the requirements of precise assembly tasks and the performance of the robot’s joints,a novel multivariable optimization method was used to shorten the execution time of any specific path to the shortest.The acceleration time was adjusted asynchronously,and the execution efficiency was optimized.Specific tests were performed on a modular 6-degree-of-freedom(DoF)robot in the optoelectronic industry.The experimental results indicate that compared with other optimal execution motion planning methods,the proposed method improves the robot’s execution trajectory speed by 39%,and has better optimization performance even in degenerate joint mode.