X. Sun, W. Yeoh and S. Koenig. Generalized Fringe-Retrieving A*: Faster Moving Target Search on State Lattices. In International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 1081-1088, 2010.

Abstract: Moving target search is important for robotics applications where unmanned ground vehicles (UGVs) have to follow other friendly or hostile UGVs. Artificial intelligence researchers have recently used incremental search to speed up the computation of a simple strategy for the hunter. The fastest incremental search algorithm, Fringe-Retrieving A*, solves moving target search problems only on two-dimensional grids, which are rather unrealistic models for robotics applications. We therefore generalize it to Generalized Fringe-Retrieving A*, which solves moving target search problems on arbitrary graphs, including the state lattices used for UGV navigation.

Download the paper in pdf.

Many publishers do not want authors to make their papers available electronically after the papers have been published. Please use the electronic versions provided here only if hardcopies are not yet available. If you have comments on any of these papers, please send me an email! Also, please send me your papers if we have common interests.

This page was automatically created by a bibliography maintenance system that was developed as part of an undergraduate research project, advised by Sven Koenig.