会议论文详细信息
2018 4th International Conference on Environmental Science and Material Application
Probe Point Selection Strategy for Lunar Rover Based on Particle Swarm Optimization
生态环境科学;材料科学
Luo, Ning^1 ; Chen, Gang^1 ; Jia, Qingxuan^1 ; Liang, Ji^2
Beijing University of Posts and Telecommunications, No.10 Xitucheng Road, Haidian District, Beijing, China^1
Key Laboratory of Space Utilization, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing
100094, China^2
关键词: Breadth first search algorithms;    Evaluation cost;    Exploration missions;    Feasible regions;    Light conditions;    Moon surface;    Optimal points;    Terrain maps;   
Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/2/022080/pdf
DOI  :  10.1088/1755-1315/252/2/022080
来源: IOP
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【 摘 要 】

In order to successfully complete the exploration mission on moon surface, it's necessary to choose a suitable probe point to plan a feasible path for lunar rover. In this paper, a probe point selection strategy is presented. The proposed strategy consists of the following three steps: Firstly, the feasible region on a given terrain map is generated by Breadth-first search algorithm based on rover travers ability; secondly, the evaluation cost of the probe point is constructed by geography information and light condition; finally, an optimal point that satisfies the constraint is selected by particle swarm optimization (PSO). In order to verify that the selected probe point can be safely arrived, the path of the rover is planned by A∗ algorithm. The experimental results show the correctness and feasibility of the proposed probe point selection strategy.

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