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An autonomous robot navigation system - integrating environmental mapping, path planning, localisation and motion controla

Published online by Cambridge University Press:  09 March 2009

J. M. Badcock
Affiliation:
Intelligent Robotics Research CentreMonash UniversityClaytonVictoria 3168 (Australia)
K. jay
Affiliation:
Intelligent Robotics Research CentreMonash UniversityClaytonVictoria 3168 (Australia)
L. Kleeman
Affiliation:
Intelligent Robotics Research CentreMonash UniversityClaytonVictoria 3168 (Australia)

Summary

This paper describes an autonomous robot vehicle which can navigate through an initially unknown obstacle field to a nominated goal or systematically map its working environment. The navigation system uses combined ultrasonic beacon/odometry based localisation, optical range finders for environmental mapping, an A path planning procedure and continuous motion control. The computational support is divided between a graphics workstation 'home base' and a PC hosted transputer array on-board. The integration of all the subsystems cited above has been achieved and many successful navigation experiments completed. Possible further developments which would enhance the capabilities of the system are also discussed.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1993

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References

Jarvis, R.A., Mobile Robot Navigation, invited Plenary Address, Proc. Third National Conference on Robotics,Melbourne, Australia(June, 1990) pp. 824.Google Scholar
Faugeras, O.D., How can vision make mobile robots come true Proc. International Symposium and Exposition on Robots,Sydney, Australia(Nov., 1988) pp. 14301461.Google Scholar
arvis, R.A., A perspective on range finding techniques for computer vision IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI–5, No. 1, 122139(March, 1983).CrossRefGoogle Scholar
ozano-Perez, T. and Wesley, M.A., An algorithm forplanning collision-free paths amongst polyhedral obstacles Commun. ACM 22, No. 10, 560570 (03, 1979).CrossRefGoogle Scholar
Jarvis, R.A., Growing polyhedral obstacles for planning collision-free paths, The Australian Computer J. 15, No.3, 103111 (08, 1983).Google Scholar
Jarvis, R.A., Collision-free trajectory planning using distance transforms Proc. National Conference and Exhibition on Robotics-1984, (August, 1984).Melbourne, Australia(August, 1984).Also in Mechanical Engineering Transactions of the Institution of Engineers, Australia, ME10, No. 2 (June, 1985) pp. 187191.Google Scholar
Jarvis, R.A. and Byrne, J.C., Robot navigation: touching, seeing and knowing 1st Australian Artificial Intelligence Congress (12 pp). Melbourne, Section e (11., 1986).Google Scholar
Preparata, F.P. and Shamos, M.J., ComputationalGeometry: An Introduction (Springer-Verlag, New York,1985).Google Scholar
Jarvis, R.A., Collision-free path planning in time varyingenvironments Proc. IEEE/RSJ International Workshop on Intelligent Robots and Systems, '89, Tsukuba, Japan(03., 1989) pp. 99106.Google Scholar
Ajay, K., A floor line rangefinding system IntelligentRobotic Research Centre, Monash University, Report MECSE89–4 (02., 1989).Google Scholar
Kleeman, L., Ultrasonic autonomous robot localisationsystem IEEE International Conference-Intelligent Robotsand Systems'89, Tsukuba,Japan(Sept., 1989) pp.212219.Google Scholar
Kleeman, L., Optimal estimation of position and heading for mobile robots using ultrasonic beacons and deadreckoning, presented at IEEE International Conferenceon Robotics and Automation NiceFrance(May, 1992).Google Scholar
Jazwinski, A.H., Stochastic Processes and Filtering Theory(Mathematics in Science and Engineering, Vol. 64)(Academic Press, New York, 1970).CrossRefGoogle Scholar
Nilsson, N.J., Problem-Solving Methods in ArtificialIntelligence (McGraw-Hill, New York, 1971).Google Scholar