Kinematic Enveloping Grasp Planning Method for Robotic Dexterous Hands and Three-Dimensional Objects

Abstract

Three-dimensional (3D) enveloping grasps for dexterous robotic hands possess several advantages over other types of grasps. However, their innate characteristics such as the several degrees of freedom of the dexterous hand, complexity of analyzing the 3D geometry of the object to be grasped or detecting the 3D contact points between the object and the hand make planning them automatically a very challenging problem. This thesis describes a new method for kinematic 3D enveloping grasp planning for a three-fingered dexterous hand. The required inputs are the geometric models of the object and hand; and the kinematic model of the hand. The outputs are the position and orientation of the palm and the angular joint positions of the fingers. The method introduces a new way of processing the 3D object. Instead of considering the object as a whole, a series of 2D slices (vertical and horizontal) of the object are used to define its geometry. This method is considerably simpler than other methods of object modeling and its parameters can be easily setup. A new idea for grading the object's 3D grasp search domain is proposed. The grading system analyzes the curvature pattern and thickness of the object and grades object regions according to their suitability for grasping. The proposed method is capable of eliminating most of the ungraspable areas of the object from the grasp search domain at the early stages of the search. This improves the overall efficiency of the search for a grasp. In modeling a dexterous hand a new method is proposed to model the fingers. In this model each finger is modeled by three articulated line segments, representing the top, centre and bottom of the finger. This model has significant benefits that it is efficient and does not need the exact coordinate of the 3D contact point between the finger and the object to analyze the feasibility of the grasp. The new grasp planning method was implemented by writing a 4300 line MATLAB program. The program has been run successfully with several 3D objects. These results are documented.