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http://dx.doi.org/10.5391/JKIIS.2009.19.3.381

Path-planning using Modified Genetic Algorithm and SLAM based on Feature Map for Autonomous Vehicle  

Kim, Jung-Min (부산대학교 전자전기공학과)
Heo, Jung-Min (부산대학교 전자전기공학과)
Jung, Sung-Young (부산대학교 전자전기공학과)
Kim, Sung-Shin (부산대학교 전자전기공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.19, no.3, 2009 , pp. 381-387 More about this Journal
Abstract
This paper is presented simultaneous localization and mapping (SLAM) based on feature map and path-planning using modified genetic algorithm for efficient driving of autonomous vehicle. The biggest problem for autonomous vehicle from now is environment adaptation. There are two cases that its new location is recognized in the new environment and is identified under unknown or new location in the map related kid-napping problem. In this paper, SLAM based on feature map using ultrasonic sensor is proposed to solved the environment adaptation problem in autonomous driving. And a modified genetic algorithm employed to optimize path-planning. We designed and built an autonomous vehicle. The proposed algorithm is applied the autonomous vehicle to show the performance. Experimental result, we verified that fast optimized path-planning and efficient SLAM is possible.
Keywords
autonomous vehicle; localization; SLAM; genetic algorithm; path-planning;
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