Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-19T07:23:50.614Z Has data issue: false hasContentIssue false

Fuzzy Qualitative Model of a Robot Sensor for Locating Three-dimensional Objects

Published online by Cambridge University Press:  09 March 2009

D.T. Pham
Affiliation:
Automation and Robotics Centre, School of Electrical, Electronics and Systems Engineering, University of Wales College of Cardiff, P.O. Box 904, Cardiff, CF1 3YH (U.K.)
K. Hafeez
Affiliation:
Automation and Robotics Centre, School of Electrical, Electronics and Systems Engineering, University of Wales College of Cardiff, P.O. Box 904, Cardiff, CF1 3YH (U.K.)

Summary

A fuzzy qualitative model of a robot sensor, presented in this paper, is for locating 3-D objects, and the location information is used to guide the movements of an industrial robot to pick up the objects. The sensor consists of a rigid platform mounted on a flexible column. Each object to be located is held rigidly with respect to the platform. The static deflections of the column and natural frequencies of vibration of the dynamic system comprising the object, platform and column are measured and processed using a mathematical model of the system to determine the location of the object. In practice, the frequency measurements have low repeatability, which leads to inconsistent location information. Also, when the orientation is in the region 80°–90° relative to a reference axis of the sensor, the mathematical model becomes ill-conditioned. In this paper, a fuzzy qualitative model of the sensor is described. The fuzzy model is designed to yield the orientation in the region where the mathematical model is unusable. Different stages for constructing the fuzzy model are described. The on-line implementation of the model is outlined and the experimental results obtained are presented.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Lee, S. and Kay, Y., “An Accurate Estimation of 3–D Position and Orientation Information of a Moving Object for Robot Stereo vision: Kaiman Filter ApproachProc. IEEE Int. Conf. on Robotics and Automation,Cincinnati, OH, U.S.A., (1990) pp. 414419.Google Scholar
2.Shekhar, S., Khatib, O. and Shimojo, M., “Object Localisation With Multiple SensorsInt. J. Robotics Research, 4, No. 6, 3454 (1988).Google Scholar
3.Specter, T.H., “A Tactile Sensing System for Robotic ManipulationInt. J. Robotics Research 9, No. 6, 2536 (1990).CrossRefGoogle Scholar
4.Stansfield, S.A., “A Robot Perceptual System Utilising Passive Vision and Active Touch”, Int. J. Robotics Research 7, No. 6, pp. 138161 (1988).CrossRefGoogle Scholar
5.Wolfe, D.F.H., Wijesoma, S.W. and Richards, R.J., “Eye to Hand Coordination for Vision Guided Robotic Pick–and–Place OperationAdvanced Manufacturing Engineering 2, 123132 (1990).Google Scholar
6.Howe, R.D., Popp, N., Akella, P., Kao, I. and Cutkosky, M.R., “Grasping, Manipulation, and Control With Tactile SensingProc. IEEE Int. Conf. Robotics and Automation,Cincinnati, OH (1990) pp. 12581263.Google Scholar
7.Pham, D.T. and Dissanayake, M.W.M.G., “Inertia–based Sensors With One and Two Degrees of FreedomProc. 5th Int. Conf. on Robot Vision and Sensory Control,Amsterdam (1985) pp. 223237.Google Scholar
8.Pham, D.T. and Dissanayake, M.W.M.G., “A Three–degree–of–freedom Inertial Sensor for Locating Parts” Proc. 15th Int. Symp. on Industrial Robots, Tokyo (1985) pp. 613629.Google Scholar
9.Pham, D.T. and Dissanayake, M.W.M.G., “Feasibility Study of a Vibratory Sensor for Locating 3–D ObjectsProc. 25th Int. Machine Tool Design and Research Conf.Birmingham, U.K. (1985) pp. 201211.Google Scholar
10.Pham, D.T. and Menendez, J., “A Six-degree–of–freedom Inertial Sensor for Locating Parts” Proc. 7th World Congress on Theory of Machines and Mechanisms, IFToMM, Seville, Spain (1987) pp. 929934.Google Scholar
11.Pham, D.T. and Menendez, J., “Development of a Six–degree–of–freedom Vibratory Device for Locating ObjectsInt. J. Machine Tools and Manufacture 28, No. 3, 197205 (1988).CrossRefGoogle Scholar
12.Pham, D.T., Hu, H. and Pote, J., “A Transputer–based System for Locating Parts and Controlling an Industrial Robot”, Robotica 8, part 2, pp. 97103 (1989).CrossRefGoogle Scholar
13.Pham, D.T. and Hafeez, K., “Dynamic Modelling of a Robot SensorInt. J. Mathematical and Computer Modelling 14, 456462 (1990).Google Scholar
14.Pham, D.T. and Hafeez, K., “An Adaptive Kalman Filter for Estimating the Location of 3–D Objects using a Robot SensorProc. 8th Int. Conf. Mathematical and Computer Modelling,Washington, DC., 1991 (In Press).Google Scholar
15.Zadeh, L.A., “Outline of a New Approach to the Analysis of Complex Systems and Decision ProcessesIEEE Trans, on Systems, Man and Cybernetics 3, No. 1, 2844 (1973).Google Scholar
16.Lee, C.C., “Fuzzy Logic in Control Systems: Fuzzy Logic Controller” Part II. IEEE Trans, on Systems, Man and Cybernetics 20, No. 2, 419435 (1990).Google Scholar
17.Yamazaki, T., “An Improved Algorithm for a Self-organising Controller and its Experimental Analysis” PhD thesis, Queen Mary College, University of London (1982).Google Scholar