Accurate insertion strategies using simple optical sensors

Peg-in-hole insertion is not only a longstanding problem in robotics but the most common automated mechanical assembly task. In this paper the authors present a high precision, self-calibrating peg-in-hole insertion strategy using several very simple, inexpensive, and accurate optical sensors. The self-calibrating feature allows the authors to achieve successful dead-reckoning insertions with tolerances of 25 microns without any accurate initial position information for the robot, pegs, or holes. The program the authors implemented works for any cylindrical peg, and the sensing steps do not depend on the peg diameter, which the program does not know. The key to the strategy is the use of a fixed sensor to localize both a mobile sensor and the peg, while the mobile sensor localizes the hole. The authors' strategy is extremely fast, localizing pegs as they are en route to their insertion location without pausing. The result is that insertion times are dominated by the transport time between pick and place operations.<<ETX>>

[1]  Edward J. Nicolson Standardizing I/O for mechatronic systems (SIOMS) using real time UNIX device drivers , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[2]  Oussama Khatib,et al.  A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..

[3]  Dinesh Manocha,et al.  Object localization using crossbeam sensing , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[4]  Daniel E. Whitney,et al.  Computer-controlled Assembly , 1978 .

[5]  Michael A. Erdmann,et al.  Using Backprojections for Fine Motion Planning with Uncertainty , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[6]  Michael A. Peshkin,et al.  Programmed compliance for error corrective assembly , 1990, IEEE Trans. Robotics Autom..

[7]  Markus Vincze,et al.  Contactless position and orientation measurement of robot end-effectors , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[8]  John F. Canny,et al.  New lower bound techniques for robot motion planning problems , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[9]  John F. Canny,et al.  "RISC" industrial robotics: recent results and open problems , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[10]  Daniel E. Whitney,et al.  Quasi-Static Assembly of Compliantly Supported Rigid Parts , 1982 .

[11]  Michael A. Erdmann,et al.  Using Backprojections for Fine Motion Planning with Uncertainty , 1986 .

[12]  Aaron S. Wallack,et al.  Geometric matching algorithm for beam scanning , 1993, Other Conferences.

[13]  John F. Canny,et al.  Planning for modular and hybrid fixtures , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[14]  Russell H. Taylor,et al.  Automatic Synthesis of Fine-Motion Strategies for Robots , 1984 .

[15]  John F. Canny,et al.  On computability of fine motion plans , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[16]  Bruce Randall Donald,et al.  A Geometric Approach to Error Detection and Recovery for Robot Motion Planning with Uncertainty , 1987, Artif. Intell..