Estimating finger contact location and object pose from contact measurements in 3D grasping

Autonomously grasping a predefined object is a topic of recent research in the field of service robotics. On the one hand, there are numerous approaches in the area of image processing concerned with recognition and localization of this object. On the other hand, a lot of work has been done in the development of planning, approaching and grasping of the object with a dextrous manipulator mounted on top of a robot arm. However, in-between locating and grasping, there are significant sources of uncertainty, e.g. estimation errors in image processing, errors in calibration of cameras and robot alone and with respect to each other, and positioning errors in the robot control. During the critical closing phase of grasping however, visual servoing and position correction is almost impossible to achieve due to obstruction of the object by the gripper. This paper presents an algorithm to locally estimate the position and orientation of the object to be grasped from contact information and a geometric description of the object. In this scenario, an object description is usually available to a sufficiently accurate extent from grasp planning.