多小型无人机协同航迹规划及其硬件在回路仿真
详细信息 查看官网全文
- 英文论文题名：Multi-SUAVs Cooperative Trajectory Planning and Hardware in Loop Simulation
- 论文作者：丛岳 ; 罗阳 ; 刘贝
- 英文论文作者：Cong Yue ; Luo Yang ; Liu bei ; UAV Technology Institute ; HIWING Techonology Academy of CASIC
- 年：2016
- 作者机构：航天三院无人机技术研究所;
- 论文关键词：协同航迹规划 ; 蚁群算法 ; 硬件在回路仿真
- 英文论文关键词：cooperated trajectory planning ; ant colony algorithm ; hardware in the loop simulation
- 会议召开时间：2016-10-31
- 会议录名称：探索 创新 交流（第7集）——第七届中国航空学会青年科技论坛文集（上册）
- 英文会议录名称：Discovery,Innovation and Communication——Proceedings of 7th CSAA Science and Technology Youth Forum
- 语种：中文
- 分类号：V279
- 学会代码：ZGHU
- 会议名称：探索 创新 交流（第7集）——第七届中国航空学会青年科技论坛
- 会议地点：中国广东中山
- 主办单位：中国航空学会
- 学会名称：中国航空学会
- 页数：8
- 文件大小：2211k
- 原文格式：O
- 会议级别：全国
摘要
本文在常规蚁群算法基础之上,生成适用于解决多小型无人机协同航迹规划问题的多种群蚁群算法,使用层次划分法对协同航迹规划问题进行了分解简化,基于小型无人机协同航迹规划问题中具有代表性的同时集结任务进行了算法仿真验证。同时利用商用开源飞行控制平台PIXHAWK和飞行仿真软件X-Plane设计并搭建了低成本的多无人机协同硬件在回路仿真平台,并使用该平台对多种群蚁群算法规划出的航点的可行性进行了分析和验证。
According to the special combat mission mode and the constraint conditions,the paper optimizes and generates the multiple-species ant colony algorithm to solve the problem of multi-SUAVs cooperative trajectory planning problem.A low cost hardware in the loop simulation platform is designed and set up based on the commercial open-source flight control platform PIXHAWK and flight simulation software X- Plane,Furthermore,used the platform validate the availability of waypoints which are planned with the multiple-species ant colony algorithm.
According to the special combat mission mode and the constraint conditions,the paper optimizes and generates the multiple-species ant colony algorithm to solve the problem of multi-SUAVs cooperative trajectory planning problem.A low cost hardware in the loop simulation platform is designed and set up based on the commercial open-source flight control platform PIXHAWK and flight simulation software X- Plane,Furthermore,used the platform validate the availability of waypoints which are planned with the multiple-species ant colony algorithm.
引文
[1]Michael Franklin.Unmanned Combat Air Vehicles;Opportunities for the Guided Weapons Industry?[R]Occasional Paper,Royal United Services Institute for Defense and Security Studies,September 2008.
[2]李猛.基于智能优化与RRT算法的无人机任务规划方法研究[D].南京航空航天大学,2012.
[3]毛云云.多飞行器协同航迹规划算法研究[D].哈尔滨:哈尔滨工业大学,2010.
[4]Szczerba R J.Threat Netting for Real-Time,Intelligent Route Planners//The Prceedings of the Information,Decision,and Control Symposium.Adelaide,Australia,1999:377-382.
[5]Jevtic A,Andina D,Jaimes A,et al.Unmanned Aerial Vehicle Route Optimization Using Ant System Algorithm[C]//System of Systems Engineering(SoSE),2010 5th International Conference on.IEEE,2010;1-6.
[6]李猛,王道波,柏婷婷,等.基于蚁群优化算法和人工势场的无人机航迹规划[J].应用科学学报,2012,30(2):215-220.
[7]林林.基于协同机制的多无人机任务规划研究[D].北京邮电大学,2013.
[8]罗德林,段海滨,吴顺详,等.基于启发式蚁群算法的协同多目标攻击空战决策研究[J].航空学报,2006,27(6):1166-1170.
[9]段海滨,马冠军,赵振宇.基于模糊规则和动态蚁群-贝叶斯网络的无人作战飞机态势评估[J].智能系统学报,2013,8(2):119-127.
[10]马冠军,段海滨,刘森琪,等.基于MAX-MIN自适应蚁群优化的无人作战飞机航路规划[J].航空学报,2008,29(1305):243-248.
[2]李猛.基于智能优化与RRT算法的无人机任务规划方法研究[D].南京航空航天大学,2012.
[3]毛云云.多飞行器协同航迹规划算法研究[D].哈尔滨:哈尔滨工业大学,2010.
[4]Szczerba R J.Threat Netting for Real-Time,Intelligent Route Planners//The Prceedings of the Information,Decision,and Control Symposium.Adelaide,Australia,1999:377-382.
[5]Jevtic A,Andina D,Jaimes A,et al.Unmanned Aerial Vehicle Route Optimization Using Ant System Algorithm[C]//System of Systems Engineering(SoSE),2010 5th International Conference on.IEEE,2010;1-6.
[6]李猛,王道波,柏婷婷,等.基于蚁群优化算法和人工势场的无人机航迹规划[J].应用科学学报,2012,30(2):215-220.
[7]林林.基于协同机制的多无人机任务规划研究[D].北京邮电大学,2013.
[8]罗德林,段海滨,吴顺详,等.基于启发式蚁群算法的协同多目标攻击空战决策研究[J].航空学报,2006,27(6):1166-1170.
[9]段海滨,马冠军,赵振宇.基于模糊规则和动态蚁群-贝叶斯网络的无人作战飞机态势评估[J].智能系统学报,2013,8(2):119-127.
[10]马冠军,段海滨,刘森琪,等.基于MAX-MIN自适应蚁群优化的无人作战飞机航路规划[J].航空学报,2008,29(1305):243-248.