| 引用本文: | 付其喜,梁晓龙,张佳强,侯岳奇.双层优化的多无人机合作式冲突探测与解脱[J].哈尔滨工业大学学报,2020,52(4):74.DOI:10.11918/201808108 |
| FU Qixi,LIANG Xiaolong,ZHANG Jiaqiang,HOU Yueqi.Cooperative conflict detection and resolution for multiple UAVs using two-layer optimization[J].Journal of Harbin Institute of Technology,2020,52(4):74.DOI:10.11918/201808108 |
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| 摘要: |
| 为解决多无人机基于航向的合作式短期冲突探测与解脱问题,提出一种局部集中双层优化的合作式方法.首先将既有冲突约束与潜在冲突约束视为同一类型约束,以保证多无人机冲突问题在最大范围内求解,并设计了基于采样的冲突探测方法；通过旋转局部坐标系减少了搜索的可行区域数量,且分析了终点约束与切线约束两种解脱约束条件；然后运用图论的方法对多无人机冲突问题进行冲突关系划分,将由机动导致的无人机额外飞行距离作为解脱代价设计了机动代价函数,为求解所设计的机动代价函数这个非线性优化问题提出了双层优化策略,即先利用随机并行梯度下降法(stochastic parallel gradient descent,SPGD)搜索航向解脱的初始可行解,再运用序列二次规划(sequential quadratic programming,SQP)求得最优解以进行最优的航向解脱. 最后运用蒙特卡洛法对算法进行了可靠性评价.结果表明,本方法能够满足在线规划的需要,在解脱开始距离Davo=τ×vi（τ=25 s）的情况下能够实现100%的冲突解脱,该方法能够在保证多无人机冲突解脱安全性的基础上减少机动消耗. |
| 关键词: 无人机 冲突解脱 双层优化 随机并行梯度下降法 序列二次规划 蒙特卡洛法 |
| DOI：10.11918/201808108 |
| 分类号:V249.1,TP29 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(7,3)； 陕西省自然科学基础研究计划(2017JQ6035) |
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| Cooperative conflict detection and resolution for multiple UAVs using two-layer optimization |
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FU Qixi1,2,LIANG Xiaolong1,ZHANG Jiaqiang1,HOU Yueqi1
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(1.Shaanxi Province Lab of Meta-synthesis for Electronic & Information System (Air Force Engineering University), Xi’an 710051, China; 2.Unit 94582 of PLA, Zhumadian 463200, Henan, China)
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| Abstract: |
| Aiming at the problem of cooperative collision detection and resolution of multi-UAVs by heading control, this paper proposes a local centralized two-layer optimization method. First, the practical conflict constraints and the potential conflict constraints are regarded as the same type of constraints to ensure that the multi-UAV conflict problem can be solved in great degree. The method of conflict detection based on sampling is designed, and the number of searching feasible regions is reduced by rotating local coordinate system, and two kinds of constraint conditions, including the terminal point constraint and the tangential constraint, are analyzed. Then, the conflict relation of multi-UAV conflict problem is divided by graph theory, and the additional flight distance caused by maneuver is taken as the cost of resolution to design the maneuver cost function. In order to solve the non-linear optimization problem of the designed maneuvering cost function, a two-layer optimization strategy is proposed. The initial feasible solution is firstly searched by Stochastic Parallel Gradient Descent (SPGD), and then the optimal solution is obtained by using Sequential Quadratic Programming (SQP). Finally, Monte Carlo method is used to evaluate the reliability of the algorithm. The simulation results show that this method can satisfy the need of online planning and can achieve 100% conflict resolution under the condition of conflict start distance Davo=τ×vi(τ=25 s). This method can reduce the maneuvering consumption on the basis of ensuring the security of multi-UAV conflict resolution. |
| Key words: UAVs collision detection and resolution two-layer optimization SPGD SQP Monte Carlo simulation |
