3D waypoint generation in a dynamic environment for an airborne launch mission

被引:0
|
作者
Dicheva, S. [1 ]
Bestaoui, Y. [1 ]
机构
[1] Univ Evry Val dEssonne, Lab IBISC, Evry, France
关键词
autonomous aircraft; waypoint generation; obstacle avoidance; VEHICLES;
D O I
10.1177/0954410011419565
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The airborne launch vehicle, studied in this article, has to find an appropriate route to reach the mission goal, considering environment requirements and system constraints, for mission safety and efficiency. A method for three-dimensional waypoint generation based on an improved version of the A* algorithm with avoidance of detected obstacles is presented in this article. As the mission proceeds, the information about the environment is regularly updated. This information is considered in the mission plan, yielding a revised sequence of waypoints, to reach one or multiple goal points, depending on their order of priority. The output of the algorithm is twofold: a dynamic waypoint generation and a shortest route refined regularly. Diverse obstacles such as turbulence zones, no-fly zones, storms, etc., are considered in the flight plan as soon as they are detected. Their locations and shapes are introduced into the path search space. The improved A* capabilities are tested via simulation in different scenarios.
引用
收藏
页码:1283 / 1297
页数:15
相关论文
共 50 条
  • [1] Planar Waypoint Generation and Path Finding in Dynamic Environment
    Jia, Daoyuan
    Hu, Cheng
    Qin, Kechen
    Cui, Xiaohui
    [J]. 2014 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI 2014), 2014, : 206 - 211
  • [2] Three-Dimensional A* Dynamic Mission Planning for an Airborne Launch Vehicle
    Dicheva, Svetlana
    Bestaoui, Yasmina
    [J]. JOURNAL OF AEROSPACE INFORMATION SYSTEMS, 2014, 11 (02): : 98 - 105
  • [3] 3D Model Generation using an Airborne Swarm
    Clark, R. A.
    Punzo, G.
    Dobie, G.
    MacLeod, C. N.
    Summan, R.
    Pierce, G.
    Macdonald, M.
    Bolton, G.
    [J]. 41ST ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 34, 2015, 1650 : 1460 - 1467
  • [4] Force generation by ocular fibroblasts and simultaneous behavioral Imaging in a dynamic 3D environment
    Dahlmann, AH
    Eastwood, M
    Bailly, M
    Khaw, PT
    [J]. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2005, 46
  • [5] HILS setup of dynamic flight path planning in 3D environment with flexible mission planning using Ground Station
    Al-Jarrah, M. A.
    Hasan, M. M.
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2011, 348 (01): : 45 - 65
  • [6] 3D Semantic VSLAM of Dynamic Environment Based on YOLACT
    Wu, Dongyan
    Xie, Bingbo
    Tao, Chongben
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [7] 3D SLAM in Dynamic Environment: an Algorithm for Mobile Robot
    Baltashov, Ilia
    Semakova, Anna
    Bakhshiev, Aleksandr
    [J]. 2020 24TH INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), 2020, : 642 - 647
  • [8] Context-Aware 3D Visualization of the Dynamic Environment
    Rivu, Sheikh Radiah
    Burschka, Darius
    [J]. 2019 2ND IEEE CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR 2019), 2019, : 42 - 47
  • [9] Accurate generation of the 3D map of environment with a RGB-D camera
    Gonzalez-Fraga, Jose A.
    Kober, Vitaly
    Diaz-Ramirez, Victor H.
    Gutierrez, Everardo
    Alvarez-Xochihua, Omar
    [J]. APPLICATIONS OF DIGITAL IMAGE PROCESSING XL, 2017, 10396
  • [10] Sparse to Dense Dynamic 3D Facial Expression Generation
    Otberdout, Naima
    Ferrari, Claudio
    Daoudi, Mohamed
    Berretti, Stefano
    Del Bimbo, Alberto
    [J]. 2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022), 2022, : 20353 - 20362