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A Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments

  • Jose Luis Sanchez-Lopez
  • Min Wang
  • Miguel A. Olivares-Mendez
  • Martin Molina
  • Holger Voos
Article
  • 158 Downloads

Abstract

Deliberative capabilities are essential for intelligent aerial robotic applications in modern life such as package delivery and surveillance. This paper presents a real-time 3D path planning solution for multirotor aerial robots to obtain a feasible, optimal and collision-free path in complex dynamic environments. High-level geometric primitives are employed to compactly represent the situation, which includes self-situation of the robot and situation of the obstacles in the environment. A probabilistic graph is utilized to sample the admissible space without taking into account the existing obstacles. Whenever a planning query is received, the generated probabilistic graph is then explored by an A discrete search algorithm with an artificial field map as cost function in order to obtain a raw optimal collision-free path, which is subsequently shortened. Realistic simulations in V-REP simulator have been created to validate the proposed path planning solution, integrating it into a fully autonomous multirotor aerial robotic system.

Keywords

Path planning Obstacle avoidance Dynamic environments Aerial robotics Multirotor UAV MAV Remotely operated vehicles Mobile robots 

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Notes

Acknowledgments

This work was supported by the “Fonds National de la Recherche” (FNR), Luxembourg, under the project C15/15/10484117 (BEST-RPAS).

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Automation and Robotics Research Group (ARG), Interdisciplinary Center for Security, Reliability and Trust (SnT)University of LuxembourgLuxembourgLuxembourg
  2. 2.Center for Automation and Robotics (CAR)CSIC-UPMMadridSpain
  3. 3.Department of Artificial IntelligenceTechnical University of Madrid (UPM)MadridSpain
  4. 4.Computer Vision and Aerial Robotics (CVAR)Technical University of Madrid (UPM)MadridSpain

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