Title :
Probabilistic hierarchical spatial model for mine locations and its application in robotic landmine search
Author :
Zhang, Yangang ; Schervish, Mark ; Choset, Howie
Author_Institution :
Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
One way to improve the efficiency of mine search, compared with a complete coverage algorithm, is to direct the search based on the spatial pattern of the minefield. This paper extends our original statistical approach (2001) to identify the regular pattern of a minefield at the beginning of the searching process. The extracted pattern parameters are used to build a probability distribution map of the configuration of the minefield. The map then can be used to guide the search for more mines efficiently. The new approach can efficiently capture the systematic and accumulated random departure of the actual mine locations from the grid pattern caused by the inaccuracy of the translational and rotational motion of the mine layer. Online implementation of our approach on a mobile robot is feasible.
Keywords :
landmine detection; mobile robots; pattern recognition; probability; search problems; mine search efficiency; minefield configuration; minefield pattern identification; minefield spatial pattern; mobile robot; probabilistic hierarchical spatial model; probability distribution map; robotic landmine search; rotational motion; statistical approach; translational motion; Cleaning; Detectors; Landmine detection; Maximum likelihood estimation; Mobile robots; Path planning; Pattern matching; Pattern recognition; Probability distribution; Robot sensing systems;
Conference_Titel :
Intelligent Robots and Systems, 2002. IEEE/RSJ International Conference on
Print_ISBN :
0-7803-7398-7
DOI :
10.1109/IRDS.2002.1041470