Planning grasps for robotic hands using a novel object representation based on the medial axis transform

Many supporting activities that future service robots might perform in people's homes depend on the capability to grasp and manipulate arbitrary objects. Easily accomplished by humans, but very difficult to achieve for robots, grasping involves dealing with a high-dimensional space of parameters which include hand kinematics, object geometry, material properties and forces. We believe that the way a robot grasps an object should be motivated by the object's geometry and that the search space for stable grasps can be dramatically reduced if the underlying object representation reflects symmetry properties of the object that contain valuable information for grasp planning. In this paper, we introduce the grid of medial spheres, a volumetric object representation based on the medial axis transform. The grid of medial spheres represents arbitrarily shaped objects with arbitrary levels of detail and contains symmetry information that can be easily exploited by a grasp planning algorithm. We present the data structure as well as a grasp planning algorithm that exploits it and provide experimental results on various object models using two robot hands in simulation.