Paint surface estimation and trajectory planning for automated painting systems

This paper investigates the problem of paint surface estimation and trajectory planning for automated painting process using a six-degree-of-freedom (6DOF) robot. We first present kinematic model 6DOF articulated spraying robot calculate coordinate transformation robot's end effector relative to base position. Then we design size joints ensure sufficient working space outer coverings automobiles. Next, stitch acquired workpiece point cloud data (PCD) perform noise reduction. The iterative closest (ICP) algorithm integrates PCD obtained from different locations into unified system. Based on features surface, compute normal vector cloud. Then, original is segmented several pieces by components axis. By slicing evenly, approximate paths each car cover. Finally, validate effectiveness our proposed through simulation.