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Robot performance measurement and calibration using a 3D computer vision system

Published online by Cambridge University Press:  09 March 2009

B. Preising  and
T. C. Hisa
B. Preising
Affiliation:
Robotics Research Laboratory, Department of Electrical and Computer Engineering, University of California, Davis, Davis, California 95616 (USA)
T. C. Hisa
Affiliation:
Robotics Research Laboratory, Department of Electrical and Computer Engineering, University of California, Davis, Davis, California 95616 (USA)
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Summary

Present day robot systems are manufactured to perform within industry accepted tolerances. However, to use such systems for tasks requiring high precision, various methods of robot calibration are generally required. These procedures can improve the accuracy of a robot within a small volume of the robot's workspace. The objective of this paper is to demonstrate the use of a single camera 3D computer vision system as a position sensor in order to perform robot calibration. A vision feedback scheme, termed Vision-guided Robot Control (VRC), is described which can improve the accuracy of a robot in an on-line iterative manner. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end effector position/orientation are actually sensed instead ofcalculated from the kinematic equations. The degree of accuracy is determined by setting a tolerance level for each of the six robot Cartesian space coordinates. In general, a small tolerance level requires a large number of iterations in order to position the end effector, and a large tolerance level requires fewer iterations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of a robot can be drastically improved. In addition, the vision system can also be used to determine the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work with an IBM Electric Drive Robot (EDR) and the proposed vision system produced a 97 and a 145 fold improvement in the position and orientation accuracy of the robot, respectively.

Keywords

3D VisionRobot performanceCalibrationPosition sensor

Information

Type
Articles
Information
Robotica , Volume 13 , Issue 4 , July 1995 , pp. 327 - 337
Copyright
Copyright © Cambridge University Press 1995

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