Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31126
Title: Fuzzy logic based active map learning for autonomous robot
Authors: Liu, J
Wang, M
Keywords: Fuzzy logic
Learning (artificial intelligence)
Mobile robots
Path planning
Issue Date: 2006
Publisher: IEEE
Source: 2006 IEEE International Conference on Fuzzy Systems, July 16-21, 2006, Vancouver, BC, p. 2134-2141 How to cite?
Abstract: The paper proposes a fast map learning approach for real-time map building and active exploration in unknown indoor environments. This approach includes a map model, a map update method, an exploration method, and a map postprocessing method. The map adopts a grid-based representation and uses frequency value to measure the confidence that a cell is occupied by an obstacle. The exploration method is implemented by coordinating two novel behaviors: path-exploring behavior and environment-detection behavior. Fuzzy logic is used to implement the behavior design and coordination. The fast map update and path planning (i.e. the exploration method) make our approach a candidate for real-time implementation on mobile robots. The results are demonstrated by simulated experiments based on a Pioneer robot with eight forward sonar sensors.
URI: http://hdl.handle.net/10397/31126
ISBN: 0-7803-9488-7
DOI: 10.1109/FUZZY.2006.1681996
Appears in Collections:Conference Paper

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