Automated Flight Technology for Integral Path Planning and Trajectory Tracking of the UAV

Mengjing Gao, Tian Yan, Wenxing Fu, Zhenfei Feng, Hang Guo

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In view of the problem that path planning and trajectory tracking are rarely solved simultaneously in the current research, which hinders their practical implementation, this paper focuses on enhancing the autonomous flight planning capability of unmanned aerial vehicles (UAVs) by investigating integrated path planning and trajectory tracking technologies. The autonomous flight process is divided into two sub-problems: waypoint designing/optimizing and waypoint tracking. Firstly, an improved DB-RRT* algorithm is proposed for waypoint planning to make the algorithm have higher planning efficiency, better optimization results, and overcome the defects of accidental and low reliability of single RRT* planning results. Secondly, the scheme of “offline design + online flight” is adopted to lead the UAV to fly online according to the waypoints’ instructions by using the sliding mode guidance based on angle constraint with finite-time convergence so that it can fly to the destination autonomously. In order to check the performance of the proposed algorithm, a variety of simulations are conducted to verify the feasibility of the proposed algorithm.

Original languageEnglish
Article number9
JournalDrones
Volume8
Issue number1
DOIs
StatePublished - Jan 2024

Keywords

  • autonomous flight technology
  • DBSCAN cluster algorithm
  • finite-time convergence
  • guidance law with angle constraints
  • improved RRT*

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