Research on Teaching System for Painting Robot Based on Binocular Stereo Vision
Chao Jiang, Xin Li, He Wen, Kou Chunrong, He Jiani · 2019
For spraying robots, the major challenge of applied research is to organize the spray track which used for spray recurrence operation. This paper proposed a new manual teaching system based on binocular stereo vision. First, the real time position data and orientation data are calculated by motive tracking system. Then, a pose data optimization method combing pauta criterion and moving average method is used, to remove abnormal value and measurement noise of the raw data. At last, optimized pose data is converting into robot joint execution code, and the spray recurrence operation of spray robot is realized. Two experiment are analyzed, which test the accuracy of color ball center position and the accuracy of yaw angle and pitch angle, respectively. The result shown that the position data error is within 2mm, and the orientation data error is within ±3 degree. Those result also display that teaching system is accuracy and visible for spraying robot track planning operation.