No abstract

Observations of human grasping [7] [6] have shown two phases: during the reaching phase of grasping, the hand preshapes in order to prepare the 'shape matching" with the object to grasp, that is the following adjusting phase. Planning grasping with dextrous robotics hands can not be summarized to these two phases. We have to split the grasping process into several phases (frequently overlapped), and also we have to look at some arising problems such as: (1) object recognition ( 2 ) planning accessibility, (3) task planning, (4) initial touch and grab phase, (5) stable grasp phase, which are consciously or unconsciously generated by a human being. A major issue addressed in this work is to integrate a part of these components in the preshaping, and in particular, the automatic planning accessibility and preshaping of objects to be grasped. The system is based on 2d analysis of slices extracted from an octree representation of objects.

Planning robust grasping operations involving a dextrous robotics hand and an object located in a three dimensional workspace requires to combine two main types of techniques: a geometric reasoning technique aimed at producing a grasping strategy (preshape of the hand, grasping parameters, type of motion to execute), and a physically based technique, allowing the analysis of the dynamic object/hand interactions. This paper focus on the second type of technique which is clearly required to conclude on the feasibility of the chosen grasping strategy (stability in particular) and to determine the execution parameters of the selected grasp (type of control to apply onto the hand in particular .nique based upon the concept of "physical models" for solving this problem. We will show how physical models can be constructed and used t o solve the assocaated stability and control strategy problems. We will also show how the related techniques has been combined with more classical geometric methods to solve the whole problem.