Path Planner for UAV Applications with Curvature Constraints: A Comparative Analysis with Other Planning Approaches.

Sensors (Basel)

Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.

Published: April 2022

This paper studies the Fast Marching Square (FM2) method as a competitive path planner for UAV applications. The approach fulfills trajectory curvature constraints together with a significantly reduced computation time, which makes it overperform with respect to other planning methods of the literature based on optimization. A comparative analysis is presented to demonstrate how the FM2 approach can easily adapt its performance thanks to the introduction of two parameters, saturation α and exponent β, that allow a flexible configuration of the paths in terms of curvature restrictions, among others. The main contributions of the method are twofold: first, a feasible path is directly obtained without the need of a later optimization process to accomplish curvature restrictions; second, the computation speed is significantly increased, up to 220 times faster than other optimization-based methods such as, for instance, Dubins, Euler-Mumford Elastica and Reeds-Shepp. Simulation results are given to demonstrate the superiority of the method when used for UAV applications in comparison with the three previously mentioned methods.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9102248PMC
http://dx.doi.org/10.3390/s22093174DOI Listing

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