| 引用本文: | 赵明,赵玲玲,苏小红,马培军,张彦航.一种三维多UAV协同航迹规划的空间模糊文化算法[J].哈尔滨工业大学学报,2015,47(10):29.DOI:10.11918/j.issn.0367-6234.2015.10.007 |
| ZHAO Ming,ZHAO Lingling,SU Xiaohong,MA Peijun,ZHANG Yanhang.A cultural algorithm with spatial Fuzzy set to solve Multi-UAVs cooperative path planning in a three dimensional environment[J].Journal of Harbin Institute of Technology,2015,47(10):29.DOI:10.11918/j.issn.0367-6234.2015.10.007 |
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| 摘要: |
| 针对多无人机在三维环境下航迹规划搜索空间大、多机协同困难等问题,提出一种基于空间模糊表示和差分进化相结合的文化算法.该方法首先用模糊集合表示三维空间网格点,提高关键路径点的被关注度；然后组合空间模糊信息、历史信息和协同信息成为文化算法的信念空间,用以剪枝规划的搜索空间；在文化算法的种群空间则利用差分进化生成满足多机协同约束的优解,并用差分获得的未知领域知识扩展信念空间,保证进化种群的多样性；最后,通过共享信息促进知识的积累和修正搜索的方向.仿真实验表明,该方法提高了关键路径点选取的效率,能够探索空间中更多的未知区域,避免求解陷入局部最优,更符合多机协同的需求,有助于快速规划出多条可行的协同航迹. |
| 关键词: 多无人机 空间模糊 文化算法 协同航迹规划 差分进化 |
| DOI：10.11918/j.issn.0367-6234.2015.10.007 |
| 分类号:TP242.6 |
| 基金项目:国家自然科学基金(7,3)；中央高校基本科研业务费专项资金资助(HIT.NSRIF.2015069). |
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| A cultural algorithm with spatial Fuzzy set to solve Multi-UAVs cooperative path planning in a three dimensional environment |
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ZHAO Ming,ZHAO Lingling,SU Xiaohong,MA Peijun,ZHANG Yanhang
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(School of Computer Science and Technology, Harbin Institute of Technology, 150001 Harbin, China)
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| Abstract: |
| The Multi-UAVs cooperative path planning has a complex search space in 3D environment, while the cooperative of Multi-UAVs is very hard to deal with. So a novel cultural algorithm based on spatial fuzzy set and differential evolution is proposed in this paper. The proposed approach uses fuzzy set to present spatial grid points in 3D, so that the key way-points on path should be paid more attention. Then the spatial fuzzy knowledge, history knowledge and cooperative knowledge that contained in the belief space of cultural algorithm prune the search space of Multi-UAVs path planning. Moreover, this approach uses differential evolution as the population space of cultural algorithm to generate the optimal solution, while it satisfies the constraints of multi-UAVs cooperative. The differential also extends the belief space with the unknown information of spatial to ensure the population diversity. In addition, the cultural algorithm exchanges the shared information, so that it accumulates the knowledge and revises the searching direction. The simulation results show that the spatial grid points based on fuzzy set enhance the efficiency of key way-points selected, and the cultural algorithm could explore more unknown space out of spatial grid such that it avoids the search fall into local optimization. Cooperative knowledge is also introduced to satisfy the requirements of Multi-UAVs cooperative to planning feasible paths for Multi-UAVs cooperative quickly. |
| Key words: Multi-UAVs spatial fuzzy cultural algorithm cooperative path planning differential evolution |
