An efficient method to compute three fingered planar object grasps using active contour models
This paper presents an efficient method to grasp an unknown planar object (disk-like object) using a three-fingered Barrett band. First, active contour models are extracted from the images taken by Biclops, a dual camera directed vision system. The centroid of each active contour model is computed, employed in triangulation, and used as an estimate of a 3-D centroid point of the object. To compute precisely where the gripper will go and how to configure the gripper to grasp the object, the active contour models are also used in a polar coordinate frame to extract concave and convex sections of the model. The proposed algorithm attempts to place the thumb in concave sections of the object, with the remaining two fingers place such that a grasp quality metric is maximized. As a consequence, the geometric properties of the object itself can improve the quality of grasp. In this work, the gripper contact is modeled as a surface rather than a point. This makes the interaction between the object and the gripper more realistic. Only a small set of inflection points are chosen as potential grasping locations. Thus the complexity of the proposed algorithm is linear as opposed to cubic if all the points on the object boundary are chosen as potential grasping locations.