Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-10T21:22:36.821Z Has data issue: false hasContentIssue false
  • English
  • Français

A Distributed–Processing Approach for Robot Dynamics Tuning

Published online by Cambridge University Press:  09 March 2009

Albert Y. Zomaya  and
Alan S. Morris
Albert Y. Zomaya
Affiliation:
Department of Electrical and Electronic Engineering, University of Western Australia, Nedlands, Perth, Western Australia 6009 (Australia).
Alan S. Morris
Affiliation:
Department of Automatic Control & Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD (UK).
Get access Rights & Permissions [Opens in a new window]

Summary

The accurate modelling of robot dynamics is essential for the design of model-based robot controllers. However, dynamic models have very complicated features which can be attributed to several reasons. For example, the continuously-varying arm configuration, uncertain effects of load handling on the dynamic stability of the arm, and the high degree of non-linearity and coupling exhibited between the different links. Hence, the accurate modelling of these effects will play an important role in the design of robust controllers. Towards this end, an efficient and fast method for the on-line tuning of robot dynamic parameters must be devised. This work proposes to solve this problem as follows. First, a simplified dynamic model of the robot is developed. The model allows for direct and straightforward extraction and regrouping of dynamic parameters. The resulting dynamic parameters are formulated as a regression equation which is linear in the dynamic parameters. Finally, the algorithm is executed using a Transputer development system to speed up the computation and meet real-time constraints. The efficiency of the approach is demonstrated by a case study.

Keywords

Robot DynamicsDynamic ParametersIdentificationVLSIParallel processingTransputers
Type
Research Article
Information
Robotica , Volume 10 , Issue 6 , November 1992 , pp. 509 - 520
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.Leahy, M.B., “Compensation of Industrial Manipulator Dynamics in the Presence of Variable Payloads” Int. J. Robotics Research 9, No. 4, 86–98 (1990).CrossRefGoogle Scholar
2.Zomaya, A. Y. and Morris, A.S., “The Dynamic Performance of Robot Manipulators Under Different Operating Conditions” IEE Proc. on Control Theory and Applications–Pt. D 137, No. 5, 281–289 (1990).CrossRefGoogle Scholar
3.Bejczy, A.K., “Robot Arm Dynamics and Control” NASA–JPL Technical Memorandum 33–669 (1974).Google Scholar
4.Luh, J.Y.S., Walker, M.W. and Paul, R.P., “On–Line Computational Scheme for Mechanical Manipulators” Trans. ASME J. Dynamic Systems, Measurements, and Control 102, 69–76 (1980).CrossRefGoogle Scholar
5.Paul, R.P., Robot Manipulators: Mathematics, Programming, and Control (MIT Press, Cambridge, Massachusetts, 1981).Google Scholar
6.Tourassis, V.D. and Neuman, C.P., “Properties and Structure of Dynamic Robot Models for Control Engineeringing Applications” Mechanism and Machine Theory 20, No. 1, 27–40 (1985).CrossRefGoogle Scholar
7.Turney, J.L., Mudge, T.N. and Lee, C.S.G., “Connection Between Formulations of Robot Arm Dynamics with Applications to Simulation and Control” Research Report RSD-TR-4–82 (Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, 1981).Google Scholar
8.Kane, T. and Levinson, D., “The Use of Kane's Dynamical Equations in Robotics” Int. J. Robotics Res. 2, No. 3, 3–21 (1983).CrossRefGoogle Scholar
9.Lee, C.S.G., Lee, B. H. and Nigam, R., “Development of the Generalized D'Alembert Equations of Motion for Mechanical Manipulators” In: Proc. 22nd Conf. Decision and Control, San Antonio, Tex., 1983) pp. 1205–1210.CrossRefGoogle Scholar
10.Lee, C.S.G. and Chung, M.J., “Adaptive Perturbation Control with Feed-Forward Compensation for Robot Manipulators” SIMULATION 44, No. 3, 127–136 (1985).CrossRefGoogle Scholar
11.Markiewicz, B.R., “Analysis of the Computed Torque Drive Method and Comparison with the Conventional Position Servo for a Compuer Controlled Manipulator” NASA-JPL Technical Memorandum Pasadena, CA 33–601 (1973).Google Scholar
12.Stone, H.W., Sanderson, A. and Neuman, C.P., “Arm Signature Identification” In: Proc. of the 1986 IEEE conf. on Robotics and Automation, San Francisco, CA. (1986) pp. 41–48.Google Scholar
13.An, C.H., Atkeson, G.G. and Hollerbach, J.M., Model-Based Control of a Robot Manipulator (MIT Press, Cambridge, Massachusetts, 1988).Google Scholar
14.Kawasaki, H. and Nishimura, K., “Terminal-Link Parameter Estimation of Robotic manipulators” IEEE J. Robotics and Automation 4, No. 5, 485–490 (1988).CrossRefGoogle Scholar
15.Khosla, P.K., “Estimation of Robot Dynamics Parameters” Int. J. Robotics and Automation 3, No. 1, 35–41 (1988).Google Scholar
16.Neuman, C.P. and Khosla, P.K., “Identification of Robot Dynamics: An Application of Recursive Estimation” In: Proc. of the 4th Yale Workshop on Application of Adaptive Systems Theory (ed. Narendra, K.S.) (Plenum Press, New York, 1986) pp. 175–194.Google Scholar
17.Olsen, H.B. and Bekey, G.A., “Identification of Robot Dynamics” In: Proc. of the IEEE Conf. on Robotics and Automation, San Francisco, CA (1986) pp. 1004–1011.Google Scholar
18.Neuman, C.P. and Murray, J.J., “Customized Computational Robot Dynamics” J. Robotic Systems 4, No. 4, 503–526 (1987).CrossRefGoogle Scholar
19.INMOS, OCCAM-2 Reference Manual (Prentice–Hall, Englewood Cliffs, New Jersey, 1988).Google Scholar
20.Jones, D.I. and Entwistle, P.M., “Parallel Computation of an Algorithm in Robotic Control” In: Int. Conf. on Control 88,Oxford, United Kingdom (1988) pp. 438–443.Google Scholar
21.Liung, L., System Identification: Theory for the User (Prentice-Hall, Englewood Cliffs, New Jersey, 1987).Google Scholar
22.Warwick, K., “Simplified Algorithms for Self-Tuning Control” In: Implementation of Self-Tuning Controllers (ed., Warwick, K.) (Peter Peregrinus Ltd. 1988) pp. 96–125.CrossRefGoogle Scholar
23.Hu, T.C., Combinatorial Algorithms (Addison-Wesley, Reading, Massachusetts, 1982).Google Scholar
24.Zomaya, A.Y. and Morris, A.S., “Dynamic Simulation and Modelling of Robot Manipulators Using Parallel Architectures” Int. J. Robotics and Automation 6, No. 3, 129–139 (1991).Google Scholar
25.Zomaya, A.Y. and Morris, A.S., “Transputer Networks for Fast Robot Dynamics” In: Robotics: Applied Mathematics and Computational Aspects (ed., Warwick, K.) (Oxford University Press, United Kingdom). In press.Google Scholar
26.Zomaya, A.Y. and Morris, A.S., “Real–Time Dynamic Simulation of Robot Manipulators” In: Proc. of the 3rd European Simulation Congress, 5–8 September, Edinburgh, Scotland, United Kingdom (eds., Murray-Smith, D., Stephenson, J., and Zobel, R.N.) (1989) pp. 588–594.Google Scholar
27.Zomaya, A.Y. and Morris, A.S., “Modelling and Simulation of Robot Dynamics Using Transputer–Based Architectures” SIMULATION (Spectral Issue on Numerical Modelling 54, No. 5, 269–278 (1990).Google Scholar