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.

[1]  John Kenneth Salisbury,et al.  Contact Sensing from Force Measurements , 1990, Int. J. Robotics Res..

[2]  Toru Omata,et al.  Fast dextrous re-grasping with optimal contact forces and contact sensor-based impedance control , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[3]  Hong Liu,et al.  DLR-Hand II: next generation of a dextrous robot hand , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[4]  Hong Liu,et al.  DLR hand II: experiments and experience with an anthropomorphic hand , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[5]  Francesco Zanichelli,et al.  Efficient exploration and recognition of convex objects based on haptic perception , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[6]  Allison M. Okamura,et al.  Haptic exploration of objects with rolling and sliding , 1997, Proceedings of International Conference on Robotics and Automation.

[7]  Hendrik Van Brussel,et al.  Recognising and locating objects with local sensors , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[8]  Gerd Hirzinger,et al.  Contact point identification in multi-fingered grasps exploiting kinematic constraints , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[9]  Yan-Bin Jia,et al.  Pose and Motion from Contact , 1999, Int. J. Robotics Res..

[10]  Kazuo Tanie,et al.  Tactile sensor based manipulation of an unknown object by a multifingered hand with rolling contact , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[11]  Antonio Bicchi,et al.  Robotic Grasping and Manipulation , 2001 .

[12]  Giovanni Ulivi,et al.  RAMSETE -Articulated and Mobile Robots for Services and Technology , 2003 .

[13]  Ronald S. Fearing,et al.  Tactile sensing for shape interpretation , 1990 .

[14]  Gerd Hirzinger,et al.  A fast and robust grasp planner for arbitrary 3D objects , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[15]  Chris Lovchik,et al.  The Robonaut hand: a dexterous robot hand for space , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[16]  Lars Petersson,et al.  Systems integration for real-world manipulation tasks , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[17]  Peter K. Allen,et al.  Using tactile and visual sensing with a robotic hand , 1997, Proceedings of International Conference on Robotics and Automation.