Human-like Visual Grasp of Unknown Objects

In this paper a method to achieve human-like grasps in unstructured environments is presented. The algorithm is composed of an object surface reconstruction algorithm and a local grasp planner, evolving in parallel. The former uses an elastic elliptical reconstruction surface, with axes and dimensions assigned by a preshaping process, that is let to evolve dynamically under the action of reconstruction forces. The reconstruction surface shrinks toward the object until some parts of the surface intercept the object visual hull. The latter moves the fingertips on the current available reconstruction surface towards points which are optimal (in a local sense) with respect to a certain number of indices weighting both the grasp quality and the kinematic configuration of the hand. A control module must ensure that the references given by the planner are correctly followed by the robotic hand. Experiments are presented, showing the effectiveness of the proposed algorithm.