Flight plan optimization of a UAV making a Hamiltonian cycle between N measurement points; Traveler problem and battery lifetime

Optimisation de plan de vol d'un drone faisant un cycle hamiltonien entre N points de mesures ; Problème du voyageur de commerce et durée de vie de batterie

Mohamed Chakchouk (1) , Abdelkhalak El Hami (1) , Pierre-Richard Dahoo (2) , Azzedine Lakhlifi (3) , Wajih Gafsi (4) , Mohamed Haddar (4)

1 INSA Rouen Normandie - Institut national des sciences appliquées Rouen Normandie
2 PLANETO - LATMOS
3 UFC - Université de Franche-Comté
4 ENIS - École Nationale d'Ingénieurs de Sfax | National School of Engineers of Sfax

Cover path planning is a fascinating area of study for roboticists, with many studies available in the research literature. During the trajectory planning phase. Since energy consumption is a function of the trajectory it will take, the energy consumption problem will be partially converted to a trajectory optimization problem. For the first phase, we will compress the problem into a 2d design, which is known as the "traveling salesman problem". There is no known method for solving the "traveling salesman problem" that provides accurate answers in a reasonable amount of time for large cases (a large number of cities). Due to the combinatorial explosion, we will often have to make do with approximate solutions for these huge situations. In this paper we will show a heuristic and make a numerical simulation of the flight plan and then characterize the effect of this optimization on the flight time.

trajectoire qu'elle va prendre, le problème de consommation d'énergie sera partiellement converti en un problème d'optimisation de trajectoire. Pour la première phase, nous comprimerons le problème en un plan 2d, qui est connu sous le nom de "problème du voyageur de commerce". Il n'existe pas de méthode connue de résolution du "problème du voyageur de commerce" qui permette d'obtenir des réponses exactes en un temps raisonnable pour les cas de grande taille (un grand nombre de villes). En raison de l'explosion combinatoire, nous devrons souvent nous contenter de solutions approximatives pour ces énormes situations. Dans cet article on va montrer une heuristique et faire une simulation numérique du plan de vol puis on va caractériser l'effet de cette optimisation sur le temps de vol. ABSTRACT. Cover path planning is a fascinating area of study for roboticists, with many studies available in the research literature. During the trajectory planning phase. Since energy consumption is a function of the trajectory it will take, the energy consumption problem will be partially converted to a trajectory optimization problem. For the first phase, we will compress the problem into a 2d design, which is known as the "traveling salesman problem". There is no known method for solving the "traveling salesman problem" that provides accurate answers in a reasonable amount of time for large cases (a large number of cities). Due to the combinatorial explosion, we will often have to make do with approximate solutions for these huge situations. In this paper we will show a heuristic and make a numerical simulation of the flight plan and then characterize the effect of this optimization on the flight time. MOTS-CLÉS. Problème du voyageur de commerce, monte Carlo, chaine de Markov, batteries durées de vie, plan de vol, optimisation. KEYWORDS. Commercial traveler problem, monte carlo, markov chain, batteries lifetime, flight plan, optimization.

Domaines: Sciences de l'ingénieur [physics]

Mohamed Chakchouk, Abdelkhalak El Hami, Pierre-Richard Dahoo, Azzedine Lakhlifi, Wajih Gafsi, et al.. Optimisation de plan de vol d'un drone faisant un cycle hamiltonien entre N points de mesures ; Problème du voyageur de commerce et durée de vie de batterie. Uncertainties and Reliability of Multiphysical Systems, 2022, 6 (1), 7p. ⟨10.21494/ISTE.OP.2022.0806⟩. ⟨insu-03602789⟩