Optimized trajectories of multi-robot deploying wireless sensor nodes

Khoufi, Ines; Hadded, Mohamed; Minet, Pascale; Laouiti, Anis

doi:10.1109/wimob.2015.7348034

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…The originality of this contribution is the simplicity of the solutions proposed. The processing time is lower than this obtained by genetic algorithm [11] because the space of solutions explored in reduced.…”

Section: Related Workmentioning

confidence: 81%

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Unmanned Aerial Vehicles path planning for area monitoring

Khoufi

Minet

Achir

2016

2016 International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN)

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In this paper we are interested in area monitoring using Unmanned Aerial Vehicles (UAVs). Basically, we propose a path planning approach for area monitoring where UAVs are considered as mobile collectors. The area to be monitored is divided into cells. The goal is to determine the path of each UAV such that each cell is covered by exactly one UAV, fairness is ensured in terms of the number of cells visited by each UAV and the path of each UAV is minimized. To meet our goal, we proceed in two steps. In the first step, we assign to each UAV the cells to visit. In the second step, we optimize the path of each UAV visiting its cells. For the first step, we propose two solutions. The first solution is based on cluster formation, each cluster is made up of the set of cells monitored by a same UAV. The second solution is based on game theory and uses coalition formation to determine the cells to be monitored by each UAV. In the second step and for both solutions, we propose to apply optimization techniques to minimize the path of each UAV that visits all its cells.

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Section: Related Workmentioning

confidence: 81%

“…In [11], we defined the MRDS problem where multiple robots are in charge of deploying wireless sensor nodes and placing them at some given positions called points of interest. The problem addressed in this paper differs from the MRDS problem by the objectives considered.…”

Section: Related Workmentioning

confidence: 99%

Unmanned Aerial Vehicles path planning for area monitoring

Khoufi

Minet

Achir

2016

2016 International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN)

Self Cite

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“…One more study in [50] proposed a multi-objective optimization problem PSO based approaches. The particle swarm optimization approach is one of the best-known meta-heuristics and has many similarities with genetic algorithms.…”

Section: Figure 1 Two Traditional Encoding Methodsmentioning

confidence: 99%

A Comprehensive Survey on the Multiple Travelling Salesman Problem: Applications, Approaches and Taxonomy

Cheikhrouhou¹

2021

Preprint

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The Multiple Travelling Salesman Problem (MTSP) is among the most interesting combinatorial optimization problems because it is widely adopted in real-life applications, including robotics, transportation, networking, etc.Although the importance of this optimization problem, there is no survey dedicated to reviewing recent MTSP contributions. In this paper, we aim to fill this gap by providing a comprehensive review of existing studies on MTSP. In this survey, we focus on MTSP’s recent contributions to both classical vehicles/robots and unmanned aerial vehicles. We highlight the approaches applied to solve the MTSP as well as its application domains. We analyze the MTSP variants and propose a taxonomy and a classification of recent studies.

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“…Ground Vehicles and Robots solutions [70] 2007 [57] 2008 [41] 2009 [78] 2010 h [71] 2011 [74] 2013 [45] 2013 [61] 2013 [75] 2014 [49] 2015 [50] 2015 [58] 2015 [64] 2015 [77] 2016 [79] 2016 b [62] 2017 a [82] 2017 j [42] 2017 [43] 2017 [31] 2018 i [48] 2018 [60] 2018 [65] 2018 [46] 2019 [38] 2019 [59] 2019 [66] 2019 [68] 2019 k [44] 2020 [51] 2020 [67] 2020 [63] 2020…”

Section: Objmentioning

confidence: 99%