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FM2 Path Planner for UAV Applications with Curvature Constraints: A Comparative Analysis with Other Planning Approaches.
Garrido, Santiago; Muñoz, Javier; López, Blanca; Quevedo, Fernando; Monje, Concepción A; Moreno, Luis.
Afiliação
  • Garrido S; Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.
  • Muñoz J; Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.
  • López B; Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.
  • Quevedo F; Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.
  • Monje CA; Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.
  • Moreno L; Robotics Lab, Department of Systems Engineering and Automation, Universidad Carlos III de Madrid, Av. Universidad 30, 28911 Madrid, Spain.
Sensors (Basel) ; 22(9)2022 Apr 21.
Article em En | MEDLINE | ID: mdl-35590865
ABSTRACT
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 ß, 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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article