Recent advances in unmanned aerial vehicles real-time trajectory planning

Author:

Allaire François Charles Joseph1,Labonté Gilles2,Tarbouchi Mohammed1,Roberge Vincent1

Affiliation:

1. Department of Electrical Engineering and Computer Engineering, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada.

2. Department of Mathematics and Computer Science and Department of Electrical Engineering and Computer Engineering, Royal Military College of Canada, Kingston, ON K7K 7B4, Canada.

Abstract

The growing interest in unmanned aerial vehicles (UAV) can be attributed to many factors, particularly the potential for them to operate beyond visual line of sight and at increasingly higher levels of autonomy. Trajectory planning defines the extent to which a vehicle is “autonomous”, therefore, to operate at high levels of autonomy, UAV will require real-time embedded trajectory planning that respects a minimum of flyability. This paper presents a review of recent advances in UAV trajectory planning and seeks to clarify the flyability, the real-time, and the embedded aspects, which are not adequately considered by previous survey papers. This work, which specifically focuses on Class II (≥150 and ≤600 kg) and Class III (>600 kg) fixed-wing UAV, analyses 60 papers from the last decade that mention some real-time achievement with respect to UAV trajectory planning. From this analysis, we highlight some challenges and some suggested orientations for future works.

Publisher

Canadian Science Publishing

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Control and Systems Engineering

Reference86 articles.

1. Allaire, F.C.J. 2007. FPGA implementation of an unmanned aerospace vehicle path planning genetic algorithm. M.A.Sc. thesis, Department of Electrical Engineering and Computer Engineering, Royal Military College of Canada, Kingston, Ont., Canada.

2. FPGA Implementation of Genetic Algorithm for UAV Real-Time Path Planning

3. Real-time dynamic trajectory smoothing for unmanned air vehicles

4. Three-Dimensional Curvature-Constrained Trajectory Planning Based on In-Flight Waypoints

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