基于多传感器数据融合的工业机器人运动路径规划研究

Research on the Motion Path Planning of Industrial Robots Based on Multi-Sensor Data Fusion

当前的工业机器人运动路径规划映射坐标建立多为定点式,路径规划效率较低,导致最优路径长度增加,为此提出基于多传感器数据融合的工业机器人运动路径规划方法。文章部署多传感节点及基础数据采集,描述机器人位姿,构建多目标映射坐标。设计多传感器数据融合机器人运动路径规划模型,采用逆向修正的方式规划路径。测试结果表明,与初始的机器人规划路径长度标准比对,该方法的最优路径长度均控制在9.5 m以下,说明工业机器人运动路径规划方法更加灵活、多变,针对性较强。

The current mapping coordinates for industrial robot motion path planning are mostly fixed point,resulting in low path planning efficiency and an increase in optimal path length.Therefore,a motion path planning method for industrial robots based on multi-sensor data fusion is proposed.Deploy multiple sensor nodes and collect basic data,describe robot pose,and construct multi-target mapping coordinates.Design a motion path planning model for multi-sensor data fusion robots,using reverse correction to achieve path planning processing.The test results show that compared with the initial robot planning path length standard,the optimal path length of this method is controlled below 9.5 m,indicating that the industrial robot motion path planning method is more flexible,versatile,and targeted.