Modified Artificial Potential Field for the Path Planning of Aircraft Swarms in Three-Dimensional Environments.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

Path planning techniques are of major importance for the motion of autonomous systems. In addition, the chosen path, safety, and computational burden are essential for ensuring the successful application of such strategies in the presence of obstacles. In this context, this work introduces a modified potential field method that is capable of providing obstacle avoidance, as well as eliminating local minima problems and oscillations in the influence threshold of repulsive fields. A three-dimensional (3D) vortex field is introduced for this purpose so that each robot can choose the best direction of the vortex field rotation automatically and independently according to its position with respect to each object in the workspace. A scenario that addresses swarm flight with sequential cooperation and the pursuit of moving targets in dynamic environments is proposed. Experimental results are presented and thoroughly discussed using a Crazyflie 2.0 aircraft associated with the loco positioning system for state estimation. It is effectively demonstrated that the proposed algorithm can generate feasible paths while taking into account the aforementioned problems in real-time applications.

Authors

  • Rafael Monteiro Jorge Alves Souza
    Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil.
  • Gabriela Vieira Lima
    Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil.
  • Aniel Silva Morais
    Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil.
  • Luís Cláudio Oliveira-Lopes
    Faculty of Chemical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil.
  • Daniel Costa Ramos
    Faculty of Electrical Engineering, Federal University of Uberlandia, Uberlandia 38408-100, Brazil.
  • Fernando Lessa Tofoli
    Department of Electrical Engineering, Federal University of Sao Joao del-Rei, Sao Joao del-Rei 36307-352, Brazil.