Smart Objects and Technologies for Social Good. Second International Conference, GOODTECHS 2016, Venice, Italy, November 30 – December 1, 2016, Proceedings

Research Article

A Heuristic Path Planning Approach for UAVs Integrating Tracking Support Through Terrestrial Wireless Networks

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  • @INPROCEEDINGS{10.1007/978-3-319-61949-1_23,
        author={Mustapha Bekhti and Nadjib Achir and Khaled Boussetta and Marwen Abdennebi},
        title={A Heuristic Path Planning Approach for UAVs Integrating Tracking Support Through Terrestrial Wireless Networks},
        proceedings={Smart Objects and Technologies for Social Good. Second International Conference, GOODTECHS 2016, Venice, Italy, November 30 -- December 1, 2016, Proceedings},
        proceedings_a={GOODTECHS},
        year={2017},
        month={7},
        keywords={},
        doi={10.1007/978-3-319-61949-1_23}
    }
    
  • Mustapha Bekhti
    Nadjib Achir
    Khaled Boussetta
    Marwen Abdennebi
    Year: 2017
    A Heuristic Path Planning Approach for UAVs Integrating Tracking Support Through Terrestrial Wireless Networks
    GOODTECHS
    Springer
    DOI: 10.1007/978-3-319-61949-1_23
Mustapha Bekhti1,*, Nadjib Achir1,*, Khaled Boussetta,*, Marwen Abdennebi1,*
  • 1: Université Paris 13, Sorbonne Paris Cité – L2TI (EA 4303)
*Contact email: bekhti.mustapha@univ-paris13.fr, nadjib.achir@univ-paris13.fr, khaled.boussetta@univ-paris13.fr, marwen.abdennebi@univ-paris13.fr

Abstract

In this paper we propose a new approach based on a heuristic search for UAVs path planning with terrestrial wireless network tracking. In a previous work we proposed and exact solution based on an integer linear formulation of the problem. Unfortunately, the exact resolution is limited by the computation complexity. In this case, we propose in this paper a new approach based on a heuristic search. More precisely, a heuristic adaptive scheme based on Dijkstra algorithm is proposed to yield a simple but effective and fast solution. In addition, the proposed solution can cover a large area and generate a set of optimum and near optimum paths according to the drone battery capacities. Finally, the simulation results show that the drone tracking is sustainable even in noisy wireless network environment.