Trajectory planning for mini unmanned helicopter in obstacle and windy environments

被引:0
|
作者
Xiang, Jinwu [1 ]
Shen, Tong [1 ]
Li, Daochun [1 ]
机构
[1] Beihang Univ, Sch Aeronaut Sci & Engn, Beijing, Peoples R China
来源
关键词
Trajectory planning; Mini unmanned helicopter; Optimum control; Pseudospectral method; Wind field; OPTIMIZATION;
D O I
10.1108/AEAT-05-2016-0080
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Purpose Obstacle and wind field are common environmental factors for mini unmanned helicopter (MUH) flight. This paper aims to develop a trajectory planning approach guiding MUH to avoid static and dynamic obstacles and to fly in steady uniform or boundary-layer wind field. Design/methodology/approach An optimal control model including a nonlinear flight dynamics model and a cubic obstacle model is established for MUH trajectory planning. Radau pseudospectral method is used to generate the optimal trajectory. Findings The approach can plan reasonable obstacle-avoiding trajectories in obstacle and windy environments. The simulation results show that high-speed wind fields increase the flight time and fluctuation of control inputs. If boundary-layer wind field exists, the trajectory deforms significantly and gets closer to the ground to escape from the strong wind. Originality/value The key innovations in this paper include a cubic obstacle model which is straightforward and practical for trajectory planning and MUH trajectory planning in steady uniform wind field and boundary-layer wind field. This study provides an efficient solution to the trajectory planning for MUH in obstacle and windy environments.
引用
收藏
页码:806 / 814
页数:9
相关论文
共 50 条
  • [41] Decentralized Deadlock-free Trajectory Planning for Quadrotor Swarm in Obstacle-rich Environments
    Park, Jungwon
    Jang, Inkyu
    Kim, H. Jin
    2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA, 2023, : 1428 - 1434
  • [42] Trajectory tracking controller for unmanned helicopter under environmental disturbances
    Serrano, Mario E.
    Gandolfo, Daniel C.
    Scaglia, Gustavo J. E.
    ISA TRANSACTIONS, 2020, 106 : 171 - 180
  • [43] Formation adaptation in obstacle-cluttered environments via MPC-based trajectory planning
    Chen, Yuda
    Li, Zhongkui
    SCIENCE CHINA-INFORMATION SCIENCES, 2024, 67 (07)
  • [44] Formation adaptation in obstacle-cluttered environments via MPC-based trajectory planning
    Yuda CHEN
    Zhongkui LI
    Science China(Information Sciences), 2024, (07) : 321 - 323
  • [45] Formation adaptation in obstacle-cluttered environments via MPC-based trajectory planning
    Yuda CHEN
    Zhongkui LI
    Science China(Information Sciences), 2024, 67 (07) : 321 - 323
  • [46] Planning Footsteps in Obstacle Cluttered Environments
    Ayaz, Yasar
    Konno, Atsushi
    Munawar, Khalid
    Tsujita, Teppei
    Uchiyama, Masaru
    2009 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, VOLS 1-3, 2009, : 156 - +
  • [47] Motion Planning in Obstacle Rich Environments
    Kim, Sung Hyun
    Bhattacharya, Raktim
    JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION, 2009, 6 (07): : 433 - 450
  • [48] Q-Learning based system for Path Planning with Unmanned Aerial Vehicles swarms in obstacle environments
    Puente-Castro, Alejandro
    Rivero, Daniel
    Pedrosa, Eurico
    Pereira, Artur
    Lau, Nuno
    Fernandez-Blanco, Enrique
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 235
  • [49] Online world modeling and path planning for an unmanned helicopter
    Andert, Franz
    Adolf, Florian
    AUTONOMOUS ROBOTS, 2009, 27 (03) : 147 - 164
  • [50] Motion planning in an uncertain environment: Application to an unmanned helicopter
    Davis, Joshua D.
    Chakravorty, Suman
    PROCEEDINGS OF THE 45TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, 2006, : 6814 - 6819