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ABSTRACT The main topic of the talk is an algorithm for autonomous search that minimizes the expected time for detecting multiple targets in a known built environment. The technique makes use of the probability distribution of the target(s) in the environment, making it feasible to incorporate any additional information, known a-priori or acquired while the search is taking place, into the search strategy. The environment is divided into a set of distinct regions and an adjacency matrix is used to describe the connections between them. Extending past optimal searcher path problems, the costs of searching any of the regions as well as the cost of travel can be arbitrarily specified. The search strategy is derived using a dynamic programming algorithm, and the work is illustrated using examples based on the search of an office environment. As a practical search strategy, optimal plans for 15 regions are generated in seconds. SPEAKER BIO I am a PhD student from the University of Technology, Sydney, under the supervision of Prof. Gamini Dissanayake. Haye Lau Email: hlau@eng.uts.edu.au URL: http://services.eng.uts.edu.au/~hlau/ |
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