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UAV Path Planning with Terrain Constraints for Aerial Scanning

  • Jinbiao Yuan
  • , Zhenbao Liu
  • , Xiaoyu Xiong
  • , Yunfeng Ai
  • , Long Chen
  • , Bin Tian
  • Northwestern Polytechnical University Xian
  • University of Chinese Academy of Sciences
  • Waytous
  • CAS - Institute of Automation

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

A global path planning method constrained by dynamics, kinematics, and terrain is proposed for Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicles (UAVs). Firstly, new constant-altitude waypoints are interpolated above the terrain based on altitude information and terrain resolution. Account for the coverage of airborne sensors over the surface area, a horizontal waypoint interpolation optimization (HOPT) is performed at positions with excessive bending in the horizontal direction. Secondly, for vertical plane optimization (VOPT), i.e., height optimization, a Soft Actor-Critic-based Particle Swarm Optimization (SAC-PSO) is employed to optimize the convergence speed of the method and achieve terrain following (TF). Thirdly, to evaluate the generated paths, a deep residual network (DRSN) is designed to mitigate the impact of optimization failures during the iteration process and improve the stability of the algorithm. Simulation experiments demonstrate the efficiency and path quality of the proposed method, while real-world tasks validate its practicality.

Original languageEnglish
Pages (from-to)1189-1203
Number of pages15
JournalIEEE Transactions on Intelligent Vehicles
Volume9
Issue number1
DOIs
StatePublished - 1 Jan 2024

Keywords

  • DRSN
  • SAC-PSO
  • UAV
  • path planning
  • terrain following

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