| 引用本文: | 齐乃明,孙小雷,董程,姚蔚然.航迹预测的多无人机任务规划方法[J].哈尔滨工业大学学报,2016,48(4):32.DOI:10.11918/j.issn.0367-6234.2016.04.005 |
| QI Naiming,SUN Xiaolei,DONG Cheng,YAO Weiran.Mission planning based on path prediction for multiple UAVs[J].Journal of Harbin Institute of Technology,2016,48(4):32.DOI:10.11918/j.issn.0367-6234.2016.04.005 |
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| 摘要: |
| 为提高无人机自主控制性能，实现任务分配与航迹规划整体架构，提出一种基于航迹预测的多无人机任务规划方法.首先，将禁飞区考虑为更接近真实场景的多边形模型；然后，使用改进A*航迹预测算法生成任意两个航迹点间障碍规避后的最短路径，利用该路径近似航迹航程作为任务分配过程的输入信息，建立目标函数，采用改进PSO算法求取最优结果；最后，使用B样条曲线平滑分配后的路径组合，生成无人机可飞行航迹.仿真结果表明，该方法能够以较高的计算速度和精度生成近似最优的任务分配结果和满足飞行约束的平滑航迹.
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| 关键词: 任务规划 航迹规划 无人机 改进A*算法 PSO算法 |
| DOI：10.11918/j.issn.0367-6234.2016.04.005 |
| 分类号:V19 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(61171189)；上海航天科技创新基金(SAST201312). |
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| Mission planning based on path prediction for multiple UAVs |
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QI Naiming1, SUN Xiaolei1,2, DONG Cheng3, YAO Weiran1
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(1.School of Astronautics, Harbin Institute of Technology, 150001 Harbin, China; 2.Shanghai Engineering Center for Microsatellites, 201203 Shanghai, China; 3.The Second Academy of CASIC 283 Factory, 100854 Beijing, China)
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| Abstract: |
| In order to improve the autonomous ability of unmanned aerial vehicles (UAVs) and achieve the integral framework of task assignment and path planning, a mission planning system based on path prediction algorithm for multiple UAVs is presented. To model obstacles more accurately, the forbidden areas are defined as polygons. Then, the optimal path segment avoiding all obstacles between two waypoints is computed by using improved A* path prediction algorithm. According to this path segment, the task assignment is determined by improved particle swarm optimization (PSO) algorithm. Finally, the B-spline method is adopted to smooth the flight path, which consists of the sequential path segments. Numerical results demonstrate that the proposed method can achieve the near-optimal task assignment and best flight routes with effectiveness of computation speed and precision.
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| Key words: mission planning path planning unmanned aerial vehicles (UAVs) improved A* algorithm particle swarm optimization (PSO) |
