Vision-guided grasping of unknown objects for service robots

We present an integrated vision-guided grasping system for service robots. Our system integrates computer vision to capture the shape of the objects, online grasp determination based on that shape, and image-based control for grasp execution. Novel techniques are presented to solve the problems concerned under the imposed resource constraints, namely, for information reduction and segmentation in image processing, strategies for grasp determination as well as vision-guided control for grasp execution. A preshaping heuristic strategy is combined with symmetry and local shape analysis. Also, the surface of contact between fingers and object is considered and a novel technique for sampling the visuomotor Jacobian is introduced. Experimental validation results are provided showing how the robot arm can efficiently and stably grasp unknown everyday objects