Efficient Trajectory Planning for WSN Data Collection with Multiple UAVs

  • D. AlejoEmail author
  • J. A. Cobano
  • G. Heredia
  • J. Ramiro Martínez-de Dios
  • A. Ollero
Part of the Studies in Computational Intelligence book series (SCI, volume 604)


This chapter discusses the problem of trajectory planning for WSN (Wireless Sensor Network) data retrieving deployed in remote areas with a cooperative system of UAVs (Unmanned Aerial Vehicles). Three different path planners are presented in order to autonomously guide the UAVs during the mission. The missions are given by a set of waypoints which define WSN collection zones and each UAV should pass through them to collect the data while avoiding passing over forbidden areas and collisions between UAVs. The proposed UAV trajectory planners are based on Genetics Algorithm (GA), RRT (Rapidly-exploring Random Trees) and RRT* (Optimal Rapidly-exploring Random Trees). Simulations and experiments have been carried out in the airfield of Utrera (Seville, Spain). These results are compared in order to measure the performance of the proposed planners.


Path Planning Planning Algorithm Trajectory Planning Path Planner Flight Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the European Commission FP7 ICT Programme under the Project PLANET (European Commission FP7-257649-ICT-2009-5) and the RANCOM Project (P11-TIC-7066) funded by the Junta de Andalucía (Spain). David Alejo is granted with a FPU Spanish fellowship from the Ministerio de Educación, Cultura y Deporte (Spain).


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • D. Alejo
    • 1
    Email author
  • J. A. Cobano
    • 1
  • G. Heredia
    • 1
  • J. Ramiro Martínez-de Dios
    • 1
  • A. Ollero
    • 1
  1. 1.University of SevilleSevilleSpain

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