Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-10T22:21:24.245Z Has data issue: false hasContentIssue false
  • English
  • Français

A modeling method for collision detection and motion planning of robots

Published online by Cambridge University Press:  09 March 2009

Chia-Ju Wu
Chia-Ju Wu
Affiliation:
Department of Electrical EngineeringNational Yunlin Institute of TechnologyTouliuYunlin 640Taiwan (R.O.C.)
Get access Rights & Permissions [Opens in a new window]

Summary

A modeling method for robots is proposed, in which a convex polyhedron is represented as a set of inequalities and a robot is represented as a union of convex polyhedrons. With this method, collision between robots can be detected by solving a set of linear programming problems at every sampling instant. By detecting possible collision at every sampling instant, a directed graph for robots is created. The motion planning problem of robots is then transformed into a path searching problem in the directed graph and can be solved by exisiting searching algorithms.

Keywords

Robots modelingCollision detectionMotion planningLinear programming.
Type
Research Article
Information
Robotica , Volume 11 , Issue 3 , May 1993 , pp. 217 - 226
Copyright
Copyright © Cambridge University Press 1993

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.Hwang, Y. K. and Ahuja, N., “Path planning using a potential field representation” Proceedings of IEEE International Conference on Robotics and Automation (1988) pp. 648–649.Google Scholar
2.Gilbert, E.G. and Johnson, D.W., “Distance functions and their application to robot path planning in the presence of obstacles” IEEE J. Robotics and Automation 1, 21–30 (1985).CrossRefGoogle Scholar
3.Kant, K. and Zucker, S.W., “Toward efficient trajectory planning. The path-velocity decomposition,” Int. J. Robotics Research 5, 72–89 (1986).CrossRefGoogle Scholar
4.Lee, B.H. and Lee, C.S.G., “Collision-free motion planning of two robots” IEEE Transactions on Systems, Man. and Cybernetics 17, 21–32 (1987).CrossRefGoogle Scholar
5.Brooks, R.A., “Solving the find-path problem by good representation of free space” IEEE Transactions on Systems, Man and Cybernetics 13, 190–197 (1983).CrossRefGoogle Scholar
6.Brooks, R.A. and Lozano-Perez, T., “A subdivision algorithm in configuration space for findpath with rotation” IEEE Transactions on Systems, Man and Cybernetics 15, 224–233 (1985).CrossRefGoogle Scholar
7.Lozano-Perez, T., “Spatial planning: A configuration space approach” IEEE Transactions on Computers 32, 108–120 (1983).CrossRefGoogle Scholar
8.Lozano-Perez, T. and Wesley, M.A., “An algorithm for planning collision-free paths among polyhedral obstacles” Communications of the ACM 22, 560–570 (1979).CrossRefGoogle Scholar
9.Udupa, S.M., “Collision detection and avoidance in computer controlled manipulators” Ph.D. Dissertation (Department of Electrical Engineering, California Institute of Technology, 1977).Google Scholar
10.Chien, R.T., Zhang, L., and Zhang, B., “Planning collision-free paths for robotic arm among obstacles” IEEE Transactions on Pattern Analysis and Machine Intelligence 6, 91–96 (1984).CrossRefGoogle ScholarPubMed
11.Iyengar, S.S., Jorgensen, C.C., Rao, S.V.N., and Weisbin, C.R., “Robot navigation algorithms using learned spatial graphs” Robotica 4, Part 2, 93–100 (1986).CrossRefGoogle Scholar
12.Lumelsky, V.J. and Stepnov, A.A., “Dynamic path planning for a mobile robot automation with limited information on the environment” IEEE Trans, on Automatic Control 31, 1058–1063 (1986).CrossRefGoogle Scholar
13.Huang, H.P. and Lee, P.C., “A real-time algorithm for obstacle avoidance of autonomous mobile robots” Robotica 10, Part 3, 217–227 (1992).Google Scholar
14.Whitesides, S., “Computational geometry and motion planning” In: Computation Geometry, Toussaint, G.T. (ed.) (Elsevier Science Publishers B.V., North-Holland, 1985).Google Scholar
15.Requicha, A.A. G., “Representations for rigid solid: Theory, methods, and systems” Computing Surveys 12, 437–464 (1980).CrossRefGoogle Scholar
16.Requicha, A.A.G., “Solid modeling: current status and research directions” IEEE Computer Graphics and Applications 3, 25–37 (1983).CrossRefGoogle Scholar
17.Foley, J. D. and Van Dam, A., Fundamentals of Interactive Computer Graphics (Addison-Wesley, Reading, Mass., 1982).Google Scholar
18.Watt, A., Fundamentals of Three-Dimensional Computer Graphics (Addison-Wesley, Reading, Mass., 1989).Google Scholar
19.Craig, J. J., Introduction to Robotics: Mechanics and Control (2nd edition, Addison-Wesley, Reading, Mass., 1989).Google Scholar
20.Horowitz, E. and Sahni, S., Data Structures in Pascal (Computer Science Press, Inc., Maryland, 1984).Google Scholar