Skip to main content
Article thumbnail
Location of Repository

Belief change maximisation for hydrothermal vent hunting using occupancy grids

By Zeyn Saigol, Richard Dearden, Jeremy Wyatt and Bramley Murton

Abstract

Abstract — The problem of where a mobile robot should go to efficiently build a map of its surroundings is frequently addressed using entropy reduction techniques. However, in exploration problems where the goal is to find an object or objects of interest, such techniques can be a useful heuristic but are optimising the wrong quantity. An example of such a problem is an autonomous underwater vehicle (AUV) searching the sea floor for hydrothermal vents. The state of the art in these problems is information lookahead in the action-observation space which is computationally expensive. We present an original belief-maximisation algorithm for this problem, and use a simulation of the AUV problem to show that our method outperforms straightforward entropy reduction and runs much faster than information lookahead while approaching it in terms of performance. We further introduce a heuristic using an orienteering-problem (OP) solver, which improves the performance of both our belief-maximisation algorithm and information lookahead

Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.193.9652
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.cs.bham.ac.uk/%7Ena... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.