Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-25T16:40:01.565Z Has data issue: false hasContentIssue false
  • English
  • Français

A Graph-Searching Approach to Trajectory Planning of Robots

Published online by Cambridge University Press:  09 March 2009

Witold Jacak ,
Ignacy Dulęba  and
Paweł Rogalinski
Witold Jacak
Affiliation:
Institute of Engineering Cybernetics, Technical University of Wroclaw, Janiszewskiego 11/17, 50–372 Wroclaw (Poland)
Ignacy Dulęba
Affiliation:
Institute of Engineering Cybernetics, Technical University of Wroclaw, Janiszewskiego 11/17, 50–372 Wroclaw (Poland)
Paweł Rogalinski
Affiliation:
Institute of Engineering Cybernetics, Technical University of Wroclaw, Janiszewskiego 11/17, 50–372 Wroclaw (Poland)
Get access Rights & Permissions [Opens in a new window]

Summary

A new method of optimal cost trajectory planning based on a graph searching algorithm is presented. Various heuristic functions which play the key role in the construction of effective algorithms for solving such problems are proposed. Some numerical examples are given based on the kinematic and dynamic models of a IRb-6 ASEA robot. This method rooted in AI has less computational complexity than a dynamical programming method applying to the same optimal-cost trajectory planning problem.

Keywords

Trajectory planningGraph searchingHeuristic functionIndustrial robots
Type
Research Article
Information
Robotica , Volume 10 , Issue 6 , November 1992 , pp. 531 - 537
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]Shin, K.G. and McKay, N.D., “Minimum–time control of robotic manipulators with geometric path constraints” IEEE Transactions AC–30, No. 6, 531–541 (1985).Google Scholar
[2]Pfeiffer, F. and Johanni, R., “A concept for manipulator trajectory planning” IEEE J. Robotics and Automation RA–3, No. 2, 115–123 (1987).CrossRefGoogle Scholar
[3]Luh, J.Y.S. and Lin, C.S., “Optimum path planning for mechanical manipulators” ASME J. Dynam. Syst., Measurement, Contr. 2, 330–335 (1981).Google Scholar
[4]Bobrow, J.E., Dubowsky, S. and Gibson, J.S., “On the optimal control of robotic manipulators with actuator constraints” Amer. Contr. Conf. (1983) pp. 782–787.Google Scholar
[5]Shin, K.G. and McKay, N.D., “A dynamic programming approach to trajectory planning of robotic manipulators” IEEE Transactions AC–31, No. 6, 491–500 (1986).Google Scholar
[6]Tan, H.H. and Potts, R.B., “A discrete planner for robotic arms with six degrees of freedom” IEEE Transactions RA–5, No. 5, 681–690 (1989).Google Scholar
[7]Jacak, W., “Strategies of searching collision–free movement of robots. A graph searching approach” Robotica 7, 129–138 (1989).CrossRefGoogle Scholar
[8]Lozano-Perez, T., “Automatic Planning of Manipulator Transfer Movements” IEEE Transactions SMC 11, 681–698 (1981).Google Scholar
[9]Nilsson, J., Principles of Artificial Intelligence (Tioga Publishing Co., California, 1980).Google Scholar
[10]Kim, B.K. and Shin, K.G., “Suboptimal control of industrial manipulators with a weighted minimum time fuel criterion” IEEE Transactions AC–30, No. 1, 1–10 (1985).Google Scholar
[11]Gosiewski, A. et al. , “Dynamic properties of IRbAC–6 and IRbAC–60 robots” Automation Dept. Reports, (Technical University of Warsaw, 1989).Google Scholar