This paper describes the development of a near-optimal fuzzy controller for maneuvering a car in a parking lot. To generate the rules of the fuzzy controller, a cell mapping method is utilized to systematically generate near-optimal trajectories for all possible initial states in the parking lot. Based on the input-output relations of these trajectories, which represent the states and controls of the corresponding cells, a set of fuzzy rules are generated automatically. In order to result in a small number of fuzzy rules from the large amount of numerical information generated by cell mapping, grouping of trajectories is proposed and each rule applies to the cells in one group. This reduces substantially the number of rules in the fuzzy controller compared with establishing the rules directly using the control data of individual cells
T. Kim and M. Leu, "Cell Mapping Based Fuzzy Control of Car Parking," Proceedings of the 1998 IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineers (IEEE), Jan 1998.
The definitive version is available at https://doi.org/10.1109/ROBOT.1998.680716
1998 IEEE International Conference on Robotics and Automation
Mechanical and Aerospace Engineering
Keywords and Phrases
Automobiles; Car Parking; Cell Mapping; Fuzzy Control; Fuzzy Rules; Near-Optimal; Path Planning; Position Control; Rule Based Systems; State Space Method; State-Space Methods; Suboptimal Control; Trajectory Control
Article - Conference proceedings
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