面向喷涂件下挂的机器人3D视觉引导策略研究

Study of 3D vision guidance strategy for robots with sprayed parts hanging down

因悬挂链运送喷涂工件难以严格定位,导致其下挂效率低下,提出一种基于3D视觉引导机器人进行喷涂件下挂的控制策略。通过实例分割网络Mask-RCNN进行训练推理,得到喷涂件实例MASK,获取经像素对齐并实例分割后的彩色图和深度图,利用相机内参重建喷涂件三维点云;离线生成喷涂件模板点云,在线生成喷涂件目标点云,经点云初始配准矫正喷涂件的位姿后,进而通过ICP精配准算法实现喷涂件位姿估计;在机器人视觉系统手眼标定之后,进一步通过5次多项式插值设计机器人关节平滑运动轨迹,控制引导机器人进行喷涂件下挂。实验结果表明,喷涂件位姿估计角度平均误差不超过10°,在Z移动方向上误差值平均为6.83 mm,最小为0.02 mm,且在仿真环境和现场环境可引导机器人实现喷涂件自主下挂。

A control strategy based on 3D vision to guide the robot for spraying parts hanging is proposed because the hanging chain transporting spraying parts is difficult to be strictly positioned,which results in its low hanging efficiency.The MASK of the sprayed part is obtained by training and inference through the instance segmentation network Mask-RCNN,and the color and depth maps are obtained after pixel alignment and instance segmentation.After the hand-eye calibration of the robot vision system,the robot joints are further designed to move smoothly by means of five polynomial interpolation,and the robot is controlled and guided to hang the sprayed parts.The experimental results show that the average error of the position angle of the sprayed parts is not more than 10°,and the average error value is 6.83 mm in the Z-movement direction,with a minimum of 0.02 mm,and the robot can be guided to realize the autonomous hanging of the sprayed parts in the simulation environment and on-site environment.