Three-dimensional path planning for unmanned aerial vehicle based on interfered fluid dynamical system
查看参考文献33篇
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文摘
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This paper proposes a method for planning the three-dimensional path for low-flying unmanned aerial vehicle (UAV) in complex terrain based on interfered fluid dynamical system (IFDS) and the theory of obstacle avoidance by the flowing stream. With no requirement of solutions to fluid equations under complex boundary conditions, the proposed method is suitable for situations with complex terrain and different shapes of obstacles. Firstly, by transforming the mountains, radar and anti-aircraft fire in complex terrain into cylindrical, conical, spherical, parallelepiped obstacles and their combinations, the 3D low-flying path planning problem is turned into solving streamlines for obstacle avoidance by fluid flow. Secondly, on the basis of a unified mathematical expression of typical obstacle shapes including sphere, cylinder, cone and parallelepiped, the modulation matrix for interfered fluid dynamical system is constructed and 3D streamlines around a single obstacle are obtained. Solutions to streamlines with multiple obstacles are then derived using weighted average of the velocity field. Thirdly, extra control force method and virtual obstacle method are proposed to deal with the stagnation point and the case of obstacles’ overlapping respectively. Finally, taking path length and flight height as sub-goals, genetic algorithm (GA) is used to obtain optimal 3D path under the maneuverability constraints of the UAV. Simulation results show that the environmental modeling is simple and the path is smooth and suitable for UAV. Theoretical proof is also presented to show that the proposed method has no effect on the characteristics of fluid avoiding obstacles. |
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来源
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Chinese Journal of Aeronautics
,2015,28(1):229-239 【核心库】
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DOI
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10.1016/j.cja.2014.12.031
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关键词
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Fluid dynamical system
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Obstacle avoidance
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Potential field
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Three-dimensional path planning
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UAV maneuverability
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Unmanned aerial vehicle
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地址
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1.
Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing, 100191
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School of Automation, Shengyang Aerospace University, Shenyang, 110136
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语种
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英文 |
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文献类型
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研究性论文 |
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ISSN
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1000-9361 |
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学科
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电子技术、通信技术 |
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基金
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国家自然科学基金
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文献收藏号
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CSCD:5420282
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参考文献 共
33
共2页
|
|
1.
Yang J. Practicality-based probabilistic roadmaps method.
2011 Canadian conference on computer and robot vision,2011:102-108
|
被引
1
次
|
|
|
|
|
2.
Zucker M. Multipartite RRTs for rapid replanning in dynamic environments.
2007 IEEE international conference on robotics and automation,2007:1603-1609
|
被引
4
次
|
|
|
|
|
3.
Mujumdar A. Evolving philosophies on autonomous obstacle/collision avoidance of unmanned aerial vehicles.
J Aerosp Comput Inform Commun,2011,8(2):17-41
|
被引
7
次
|
|
|
|
|
4.
Chen M. A modified ant optimization algorithm for path planning of UCAV.
Appl Soft Comput,2008,8(4):1712-1718
|
被引
15
次
|
|
|
|
|
5.
Zhao L. Optimal flight path planner for an unmanned helicopter by evolutionary algorithms.
AIAA guidance, navigation and control conference and exhibit,2007:3716-3739
|
被引
1
次
|
|
|
|
|
6.
Hao Y. Real-time obstacle avoidance method based on polar coordination particle swarm optimization in dynamic environment.
2007 2nd IEEE conference on industrial electronics and applications,2007:1612-1617
|
被引
1
次
|
|
|
|
|
7.
Foo J L. Threedimensional path planning of unmanned aerial vehicles using particle swarm optimization.
11th AIAA/ISSMO multidisciplinary analysis and optimization conference,2006:992-1001
|
被引
1
次
|
|
|
|
|
8.
Duan H B. Three-dimension path planning for UCAV using hybrid meta-heuristic ACO-DE algorithm.
Proceedings of Asia simulation conference-7th international conference on system simulation and scientific computing,2009:919-924
|
被引
1
次
|
|
|
|
|
9.
Darrah M A. Increasing UAV task assignment performance through parallelized genetic algorithms.
AIAA 2007 infotech@aerospace conference and exhibit,2007:7-10
|
被引
1
次
|
|
|
|
|
10.
Frazzoil E. Maneuver-based motion planning for nonlinear systems with symmetries.
IEEE Trans Rob,2005,21(6):1077-1091
|
被引
6
次
|
|
|
|
|
11.
Karimi J. Optimal maneuver-based motion planning over terrain and threats using a dynamic hybrid PSO algorithm.
Aerosp Sci Technol,2013,26(1):60-71
|
被引
12
次
|
|
|
|
|
12.
Gong Q. Pseudospectral motion planning for autonomous vehicles.
J Guid Control Dynam,2009,32(3):1039-1045
|
被引
6
次
|
|
|
|
|
13.
Dever C. Nonlinear trajectory generation for autonomous vehicles via parameterized maneuver classes.
J Guid Control Dynam,2006,29(2):289-302
|
被引
2
次
|
|
|
|
|
14.
Nikolos I K. Evolutionary algorithm based offline/online path planner for UAV navigation.
IEEE Trans Syst Man Cybern Part B: Cybern,2003,33(6):898-912
|
被引
37
次
|
|
|
|
|
15.
Mattei M. Smooth flight trajectory planning in the presence of no-fly zones and obstacles.
J Guid Control Dynam,2010,33(2):454-462
|
被引
4
次
|
|
|
|
|
16.
Khaitib O. Real-time obstacle avoidance for manipulators and mobile robots.
Int J Robot Res,1986,5(1):90-98
|
被引
2
次
|
|
|
|
|
17.
Paul T. Modeling of UAV formation flight using 3D potential field.
Simul Model Pract Theory,2008,16(9):1453-1462
|
被引
19
次
|
|
|
|
|
18.
Scherer S. Flying fast and low among obstacles: methodology and experiments.
Int J Robot Res,2008,27(5):549-574
|
被引
6
次
|
|
|
|
|
19.
Kim J. Real-time obstacle avoidance using harmonic potential functions.
IEEE Trans Robot Autom,1992,8(3):338-349
|
被引
17
次
|
|
|
|
|
20.
Park M G. Obstacle avoidance for mobile robots using artificial potential field approach with simulated annealing.
IEEE international symposium on industrial electronics,2001:1530-1535
|
被引
5
次
|
|
|
|
|
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