计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220700079-7.doi: 10.11896/jsjkx.220700079

• 人工智能 • 上一篇    下一篇

基于多元约束Petri网的水利测绘无人机路径规划

姚喜, 陈衍德   

  1. 山东省水利勘测设计院 济南 250013
  • 出版日期:2023-06-10 发布日期:2023-06-12
  • 通讯作者: 姚喜(594318623@qq.com)

Path Planning of Hydrographic Mapping UAV Based on Multi-constraint Petri Net

YAO Xi, CHEN Yande   

  1. Shandong Survey and Design Institute of Water Conservancy,Jinan 250013,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:YAO Xi,born in 1984,postgraduate,senior engineer.Her main research interests include data processing,equipment design of mapping UAV,photogrammetry and remote sensing.

摘要: 随着测绘技术的不断发展,测绘无人机在水利工程中的应用不断深入。利用无人机进行测绘作业,一方面革新了测绘作业工作模式,提高了工作效率;另一方面也因无人机无人驾驶、持续飞行时间有限、航测图片拼接约束等客观原因,需要进行科学的无人机测绘作业路径规划,满足无人机飞行安全、航测数据有效及作业效率优化等要求。鉴于此,提出了一种基于多元约束Petri网的水利测绘无人机路径规划方法。对问题场景进行了描绘;定义了多元约束Petri网,并给出了可达性分析方法;构建了面向测绘无人机路径规划的多元约束Petri网模型;基于可达标识图析出了路径规划最优方案。实验证明了所提方法在面向水利测绘无人机的路径规划方案寻优上具有优越性。

关键词: 多元约束Petri网, 水利测绘, 无人机, 路径规划, 可达性分析

Abstract: With the development of surveying and mapping technology,the application of unmanned aerial vehicle(UAV) in hydraulic engineering has been deepened.The use of UAV has revolutionized the working mode of surveying and improved working efficiency.Due to the reasons such as unmanned aerial vehicle,limited duration of flight and restriction of aerial survey picture splice,it is necessary to carry out scientific route planning.It can meet the requirements of flight safety,validity of survey data and operation efficiency.In view of this,a path planning method based on multi-constraint Petri net is proposed.The problem scene is described.The multi-constraint Petri net is defined and the method of reachability analysis is given.The multi-constraint Petri net model for path planning is constructed.The optimal route planning scheme is obtained based on the reachability marking diagram.Experimental results show that this method has superiority in UAV path planning scheme optimization.

Key words: Multi-constraint Petri net, Hydrographic mapping, UAV, Path planning, Reachability analysis

中图分类号: 

  • TP311
[1]YU D X.Exploring the application of tilt photography in hy-draulic engineering mapping[J].Pearl River Water Transport,2021(23):103-104.
[2]MAO J C,ZHAO S J.Research on the application of low-altitude remote sensing in hydraulic engineering mapping[J].Architectural Technology Development,2020,47(19):85-86.
[3]TIAN Z,MEGHDAD H S,AYMAN H.Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems[J].ISPRS Journal of Photogrammetry and Remote Sensing,2021,180(4):336-356.
[4]LIU C T,GUO,Y,LI N,et al.Multiuser Oriented Multi-UAV Mission Assignment With Cooperative Information Sharing[J].IEEE Wireless Communications Letters,2021,10(4):907-911.
[5]WANG J F,JIA G W,LIN J C,et al.Cooperative task allocation for heterogeneous multi-UAV using multi-objective optimization algorithm[J].Journal of Central South University,2020,27(2):432-448.
[6]MA Y H,ZHAO Y F,BAI S Y,et al.Collaborative task allocation of heterogeneous multi-UAV based on improved CBGA algorithm[C]//16th IEEE International Conference on Control,Automation,Robotics and Vision(ICARCV 2020).2020:795-800.
[7]XU L F,YANG Z Z,HUANG Z S,et al.Route design method of plant protection UAV combined with hybrid particle swarm optimization algorithm[J].Small microcomputer system,2020,41(9):1826-1832.
[8]GEBREHIWOT A A,BENI L H.Three-Dimensional Inundation Mapping Using UAV Image Segmentation and Digital Surface Model[J].ISPRS International Journal of Geo-Information,2021,10(3):139-144.
[9]XUE Z T,CHEN J,ZHANG Z C,et al.Multi-UAV coverage path planning based on optimization of convex division of complex plots[J].Acta Aeronautica et Astronautica Sinica,2022,43(X):325990.
[10]LIAO C C.Research on multi-uav cooperative mission planning[D].Chengdu:Sichuan University,2021.
[11]DENG M,CHEN Z.Coordinated path planning for multiple uavs based on k-degree smoothing[J].Computer Engineering and Design,2021,42(8):2387-2394.
[12]HE J R,HE G J,YU X S.The UAV path planning based on improved artificial bee colony algorithm[J].Fire Control & Command Control,2021,46(10):103-106.
[13]GUO Q C,DU X Y,ZHANG Y Y,et al.Three-dimensional path planning for UAV based on improved whale algorithm[J].Computer Science,2021,48(12):304-311.
[14]PANDEY P,SHUKLA A,TIWARI R.Three-dimensional path planning for unmanned aerial vehicles using glowworm swarm optimization algorithm[J].International Journal of System Assurance Engineering and Management,2018,9(4):836-852.
[15]NIELSEN L D,SUNG I,NIELSEN P.Convex decompositionfor a coverage path planning for autonomous vehicles:interior extension of edges[J].Sensors,2019,19(19):4165-4716.
[16]DEWANGAN R K,SHUKLA A,GODFREY W W.Three dimensional path planning using Grey wolf optimizer for UAVs[J].Applied Intelligence,2019,49(6):2201-2217.
[17]HASSAN M,LIU D K.PPCPP:a predator-prey-based approach to adaptive coverage path planning[J].IEEE Transactions on Robotics,2020,36(1):284-301.
[18]ZHANG S C.Path planning for multiple uavs based on reinforcement learning[D].Chengdu:Sichuan University,2021.
[19]YAO C P,XU J,LI X Y.Terrain monitoring of unmanned aerial vehicle formation[J].Science and Technology Information in China,2020(22):68-69.
[20]DU Y Y,NING Y H,LIANG Q.Reachability analysis of Logic Petri Nets using incidence matrix[J].Enterprise Information Systems,2014,8(6):630-647.
[21]DU Y Y,YNING H.Property analysis of Logic Petri Nets using reachable marking graphs[J].Frontiers of Computer Science in China,2014,8(4):684-692.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!