Range image segmentation combining edge-detection and region-growing techniques with applications sto robot bin-picking using vacuum gripper

A new segmentation algorithm that can be used for robot applications is presented. The input images are dense range data of industrial parts. The image is segmented into a number of surfaces. The segmentation algorithm uses residual analysis to detect edges, then a region-growing technique is used to obtain the final segmented image. The use of the segmentation output for determining the best holdsite position and orientation of objects is studied. As compared to techniques based on intensity images, the use of range images simplifies the holdsite determination. This information can then be used to instruct the robot to grip the object and move it to the required position. The performance of the algorithm on a number of range images is presented