基于NURBS和GOBL-ACDE的航迹规划算法
V279; 针对复杂地形条件下无人机低空突防动态航迹规划实时性及精确性的问题,提出了基于广义反向学习的自适应约束差分进化(generalized opposition-based learning adaptive constrained differential evolution, GOBL-ACDE)算法,结合非均匀有理B样条(non-uniform rational B-spline,NURBS)平滑策略,提高了多威胁复杂地形下动态航迹规划的精确性、高效性及适航性.首先,构建航迹规划任务模型,建立目标代价及约束限制函数,提出一种高度转换方法,有效提高低空突防能力;其次,将NURBS平滑...
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| Published in | 系统工程与电子技术 Vol. 42; no. 5; pp. 1073 - 1082 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
海军航空大学青岛校区航空仪电控制工程与指挥系,山东青岛,266041
01.05.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-506X |
| DOI | 10.3969/j.issn.1001-506X.2020.05.14 |
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| Abstract | V279; 针对复杂地形条件下无人机低空突防动态航迹规划实时性及精确性的问题,提出了基于广义反向学习的自适应约束差分进化(generalized opposition-based learning adaptive constrained differential evolution, GOBL-ACDE)算法,结合非均匀有理B样条(non-uniform rational B-spline,NURBS)平滑策略,提高了多威胁复杂地形下动态航迹规划的精确性、高效性及适航性.首先,构建航迹规划任务模型,建立目标代价及约束限制函数,提出一种高度转换方法,有效提高低空突防能力;其次,将NURBS平滑策略与B样条插值以及贝塞尔曲线对比分析;再次,应用广义反向学习、自适应排序变异及自适应权衡模型,改善约束条件下算法动态性、收敛性及寻优性能;最后,通过静态与动态环境对比仿真试验,验证了所提方法在多威胁复杂地形下寻优精度高、鲁棒性强、动态性好以及可靠性优的特点,能够规划出精确、高效、适航的低空突防航迹. |
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| AbstractList | V279; 针对复杂地形条件下无人机低空突防动态航迹规划实时性及精确性的问题,提出了基于广义反向学习的自适应约束差分进化(generalized opposition-based learning adaptive constrained differential evolution, GOBL-ACDE)算法,结合非均匀有理B样条(non-uniform rational B-spline,NURBS)平滑策略,提高了多威胁复杂地形下动态航迹规划的精确性、高效性及适航性.首先,构建航迹规划任务模型,建立目标代价及约束限制函数,提出一种高度转换方法,有效提高低空突防能力;其次,将NURBS平滑策略与B样条插值以及贝塞尔曲线对比分析;再次,应用广义反向学习、自适应排序变异及自适应权衡模型,改善约束条件下算法动态性、收敛性及寻优性能;最后,通过静态与动态环境对比仿真试验,验证了所提方法在多威胁复杂地形下寻优精度高、鲁棒性强、动态性好以及可靠性优的特点,能够规划出精确、高效、适航的低空突防航迹. |
| Author | 周思羽 吴文海 郭晓峰 |
| AuthorAffiliation | 海军航空大学青岛校区航空仪电控制工程与指挥系,山东青岛,266041 |
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| Author_FL | ZHOU Siyu GUO Xiaofeng WU Wenhai |
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| DocumentTitle_FL | Path planning algorithm based on NURBS and GOBL-ACDE |
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| Keywords | 威胁回避 低空突防 动态规划 差分进化 非均匀有理B样条 |
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| Publisher | 海军航空大学青岛校区航空仪电控制工程与指挥系,山东青岛,266041 |
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| Title | 基于NURBS和GOBL-ACDE的航迹规划算法 |
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