Multi-target visual recognition and positioning methods for sorting robots

Abstract

Abstract Aiming at the problems of complex shape and random placement of sorting robots, this paper proposes a multi-objective visual recognition and positioning methods for sorting robots. A sorting robot system with visual perception was constructed,which based on the four-degree-of-freedom DOBOT robot. What’s more, the visual system acquires images of multiple targets on the conveyor belt, the image preprocessing algorithm improves the contrast of the sorting targets, thus circular and linear structural elements are constructed in order to fill and smooth the multi-target regions segmented by the largest inter-class variance method. Besides, Establishing centroid coordinates based on image information to identify and locate connected domains of multi-target regions. The experimental results show that the method can achieve statistics on the number of multi-targets. On the basis of the hand-eye calibration of the sorting robot, the multi-objects with complex shapes and random positions are identified and positioned, and the positional information provides the autonomous grasping and sorting for the sorting robot.