Local perception and navigation for mobile robots
We review the main features of the software architectures of current mobile robot systems, giving special attention to the role of the perception system, and to the spatial representations used. We also mention some of the debate on world modeling and multisensor fusion issues that is presently going on.
Then we address the particular case of outdoor applications in partially unknown and partially unpredictable environments, and present our views about the development of an efficient perception system for these types of application.
KeywordsCovariance Transportation Drilling Assure Cylin
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- 1.R. Brooks, “A robust layered control system for a mobile robot”, IEEE Journal of Robotics and Automation, RA-2, April, 14–23, 1986.Google Scholar
- 2.O. Kathib, “Real time obstacle avoidance for manipulators and mobile robots”, IEEE Conference on Robotics and Automation, St Louis, March 1985.Google Scholar
- 3.B. H. Krogh, “A generalized potential field approach to obstacle avoidance control”, Robotics Research: The Next Five Years and Beyond, SME, Dearborn Michigan 1984.Google Scholar
- 4.J. Crowley, “Path planning and obstacle avoidance (a survey)”, RR LIFIA N. 46, January 1986.Google Scholar
- 5.D. T. Kuan, J. C. Zamiska, R. A. Brooks, “Natural decomposition of free space for path planning”, IEEE Conference on Robotics and Automation, St. Louis, March 1985.Google Scholar
- 6.L. P. Kaelbling, “An architecture for intelligent reactive systems”, Tech. Note 400, SRI International, October 1986.Google Scholar
- 7.P. Smolensky, “Information processing in dynamical systems: foundations of harmony theory”, Parallel Distributed Processing, Vol. 1, MIT Press 1988.Google Scholar
- 8.A. Elfes, “Using occupancy grids for mobile robot perception and navigation”, Computer, June 1989.Google Scholar
- 9.R. Chatila, J.-P. Laumond, “Position referencing and consistent world modeling for mobile robots”, IEEE Conference on Robotics and Automation, St. Louis, March 1985.Google Scholar
- 10.C.M. Witowski, “A parallel processor algorithm for robot route planning”, Proceedings of IJCAI, Karlsruhe, 1983.Google Scholar
- 12.D. E. Rumelhart, G. E. Hinton, R. J. Williams, “Learning internal representation by error propagation”, Parallel Distributed Processing, vol 1, chap 8, MIT Press, Cambridge, Massachusetts, 1986.Google Scholar