2010
DOI: 10.1108/00022661011053409
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Fast trajectory planning based on in‐flight waypoints for unmanned aerial vehicles

Abstract: Purpose -The purpose of this paper is to propose an efficient algorithm for trajectory planning of unmanned aerial vehicles (UAVs) in 2D spaces. This paper has been motivated by the challenge to develop a fast trajectory planning algorithm for autonomous UAVs through mid-course waypoints (WPs). It is assumed that there is no prior knowledge of these WPs, and their configuration is computed as in-flight procedure. Design/methodology/approach -Since the off-line techniques cannot be applied, it is required to ap… Show more

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Cited by 12 publications
(12 citation statements)
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“…The path generation incorporates the steady-state ight for straight-line paths and steady turning ight to generate circular arc trajectories. In another research, with no prior knowledge of WPs, Babaei and Mortazavi [9] o ered an online 2D trajectory-planning method. In a recent study, Lin et al proposed a fast obstacle avoidance algorithm based on the geometric approach.…”
Section: Decoupled Trajectory Planningmentioning
confidence: 99%
See 1 more Smart Citation
“…The path generation incorporates the steady-state ight for straight-line paths and steady turning ight to generate circular arc trajectories. In another research, with no prior knowledge of WPs, Babaei and Mortazavi [9] o ered an online 2D trajectory-planning method. In a recent study, Lin et al proposed a fast obstacle avoidance algorithm based on the geometric approach.…”
Section: Decoupled Trajectory Planningmentioning
confidence: 99%
“…Eqs. (8),(9), and (20) de ne the problem inequality constraint. The cost function expressed in Relation (10) should be modi ed in accordance with the transformed problem.…”
mentioning
confidence: 99%
“…Assuming perfect modelling, derivation of the dynamic inversion control law is a matter of setting the commanded rates in Equations (12)- (14) equal to the associated actual rates and solving for T c , α c and ϕ c . The computed thrust, angle-of-attack and bank angle become the commanded values needed for Equations (9)- (11). Setting Equation (1) equal to Equation (12) and solving for thrust, results in:…”
Section: Aircraft Dynamic Modellingmentioning
confidence: 99%
“…The optimal path is obtained by minimizing the cost subject to constrains (Kim et al, 2008;Babaei and Mortazavi, 2010). Path planning level consists of two phases: risk region and safety region.…”
Section: Mission Programming Levelmentioning
confidence: 99%