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J. KIMS Technol > Volume 20(6); 2017 > Article
Journal of the Korea Institute of Military Science and Technology 2017;20(6):803-812.
DOI: https://doi.org/10.9766/KIMST.2017.20.6.803   
Genetic Algorithm Based 3D Environment Local Path Planning for Autonomous Driving of Unmanned Vehicles in Rough Terrain
SeungJae Yun, Mooncheol Won
Department of Mechatronics Engineering, Chungnam National University
무인 차량의 험지 자율주행을 위한 유전자 알고리즘 기반 3D 환경 지역 경로계획
윤승재, 원문철
충남대학교 메카트로닉스공학과
Abstract
This paper proposes a local path planning method for stable autonomous driving in rough terrain. There are various path planning techniques such as candidate paths, star algorithm, and Rapidly-exploring Random Tree algorithms. However, such existing path planning has limitations to reflecting the stability of unmanned ground vehicles. This paper suggest a path planning algorithm that considering the stability of unmanned ground vehicles. The algorithm is based on the genetic algorithm and assumes to have probability based obstacle map and elevation map. The simulation result show that the proposed algorithm can be used for real-time local path planning in rough terrain.
Key Words: Local Path Planning, Genetic Algorithm, Autonomous Driving, Rough Terrain, Unmanned Ground Vehicle
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