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Content Provider | IEEE Xplore Digital Library |
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Author | Gao, M. Zhou, M. |
Copyright Year | 2005 |
Description | Author affiliation: Dept. of Math. & Comput. Sci., Seton Hall Univ., South Orange, NJ, USA (Gao, M.) |
Abstract | Autonomous mobile vehicles rely on sensors as a primary perception mechanism. Multiple sensors are used to tolerate certain types of errors and inaccuracy due to system faults and uncertain environment. An autonomous vehicle should be able to detect the dependability of various sensor data and choose the best control strategy based on its internal state and the external environment. This paper proposes a fuzzy rule based control strategy selection approach for mobile navigation in a dynamic real world environment. Fuzzy reasoning Petri nets are used for system modeling and parallel reasoning. The control strategy combining the most dependable sensor data can be chosen quickly based on the proposed approach. Case studies are provided to illustrate and verify the approach. |
Starting Page | 1651 |
Ending Page | 1656 |
File Size | 278106 |
Page Count | 6 |
File Format | |
ISBN | 0780392981 |
DOI | 10.1109/ICSMC.2005.1571385 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-10-12 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Remotely operated vehicles Mobile robots Vehicle dynamics Sensor systems Vehicle detection Fuzzy control Navigation Fuzzy reasoning Petri nets Modeling mobile vehicles Fuzzy Reasoning Petri Nets decision making environment modeling navigation |
Content Type | Text |
Resource Type | Article |
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