Recent advances in unmanned aerial vehicles real-time trajectory planning

Allaire, François C. J.; Labonté, Gilles; Tarbouchi, Mohammed; Roberge, Vincent

doi:10.1139/juvs-2017-0004

Cited by 12 publications

(9 citation statements)

References 99 publications

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“…Because of its scalability, limited computational complexity, and adaptability, it has been used previously in the course of realtime adaptive path planning for obstacle avoidance (48) and target detection and tracking (49,50). The interested reader is referred to summaries on path planning for UAVs (46,47,(51)(52)(53)(54)(55)(56)(57)(58)(59)(60)(61).…”

Section: Classification-driven Adaptive Searchmentioning

confidence: 99%

An autonomous drone for search and rescue in forests using airborne optical sectioning

2021

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Autonomous drones will play an essential role in human-machine teaming in future search and rescue (SAR) missions. We present a prototype that finds people fully autonomously in densely occluded forests. In the course of 17 field experiments conducted over various forest types and under different flying conditions, our drone found, in total, 38 of 42 hidden persons. For experiments with predefined flight paths, the average precision was 86%, and we found 30 of 34 cases. For adaptive sampling experiments (where potential findings are double-checked on the basis of initial classification confidences), all eight hidden persons were found, leading to an average precision of 100%, whereas classification confidence was increased on average by 15%. Thermal image processing, classification, and dynamic flight path adaptation are computed on-board in real time and while flying. We show that deep learning–based person classification is unaffected by sparse and error-prone sampling within straight flight path segments. This finding allows search missions to be substantially shortened and reduces the image complexity to 1/10th when compared with previous approaches. The goal of our adaptive online sampling technique is to find people as reliably and quickly as possible, which is essential in time-critical applications, such as SAR. Our drone enables SAR operations in remote areas without stable network coverage, because it transmits to the rescue team only classification results that indicate detections and can thus operate with intermittent minimal-bandwidth connections (e.g., by satellite). Once received, these results can be visually enhanced for interpretation on remote mobile devices.

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Section: Classification-driven Adaptive Searchmentioning

confidence: 99%

An autonomous drone for search and rescue in forests using airborne optical sectioning

2021

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“…Notons en deuxième lieu les trois étapes de la planification de trajectoires (telles qu'indiquées par Allaire et al (2019) et Goerzen et al (2010)) :…”

Section: Trois éTapes De La Planification De Trajectoires De Uavunclassified

“…Zheng et al (2003), Cocaud (2006), Roberge (2011) et Wang et al (2014) ont chacun utilisé l'algorithme génétique pour la planification de trajectoire d'UAV utilisant une fonction d'évaluation pour couvrir un grand nombre de critère de volabilité et d'optimisation tout en visant à performer les calculs en temps réel. Une analyse détaillée de ces différentes approches a été complétée par Allaire et al (2019). Cette analyse met en évidence l'approche rigoureuse de Roberge (2011) qui se démarque des autres recherches en présentant une fonction d'évaluation de trajectoires qui couvre quatre critères de volabilité essentiels à une trajectoire d'UAV à voilure fixe (lissage de la trajectoire, collision avec le terrain, puissance, consommation de carburant) en plus de certains critères d'optimisation (zone dangereuse, longueur et altitude) se basant sur les résultats de la recherche de Labonté (2012de Labonté ( , 2015de Labonté ( , 2016de Labonté ( , 2017ade Labonté ( , 2017b.…”

Section: éVolution Des Fonctions D'évaluation De Trajectoires D'uavunclassified

“…La planification de trajectoires en temps réel est un élément essentiel à l'autonomie des véhicules aériens sans pilote (UAV) (Huang et al 2005). Malgré les milliers d'ouvrages publiés sur la planification de trajectoires, c'est encore aujourd'hui un défi à atteindre (Allaire et al 2019). Comme le soulignent Goerzen et al (2010), Kendoul (2012) et Allaire et al (2019), ceci s'explique entre autres par le manque d'un point de référence pour permettre des comparaisons rigoureuses des différentes techniques existantes de planification de trajectoires et ainsi permettre d'accélérer les avancements dans ce domaine.…”

Section: Introductionunclassified

“…Malgré les milliers d'ouvrages publiés sur la planification de trajectoires, c'est encore aujourd'hui un défi à atteindre (Allaire et al 2019). Comme le soulignent Goerzen et al (2010), Kendoul (2012) et Allaire et al (2019), ceci s'explique entre autres par le manque d'un point de référence pour permettre des comparaisons rigoureuses des différentes techniques existantes de planification de trajectoires et ainsi permettre d'accélérer les avancements dans ce domaine. Cette absence de point de référence est entre autres due au fait que les missions des UAV sont très variées, ce qui implique des objectifs variés à ajuster lors de la planification (Dadkhah et Mettler 2012).…”

Section: Introductionunclassified

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Point de référence pour la planification de trajectoires d’UAV à voilure fixe

Allaire

Labonté

Roberge

et al. 2021

J. Unmanned Veh. Sys.

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Les revues étendues de la littérature sur la planification de trajectoires s’entendent toutes sur un point commun : le manque d’un point de référence pour permettre de comparer les différentes mises-en-œuvre dans ce domaine. Ce travail présente une fonction d’évaluation de trajectoires de véhicules aériens sans pilote (UAV) à voilure fixe qui couvrent quatre critères de volabilité essentiels et trois critères d’optimisation qui peuvent être applicables à une grande variété de mission tout en étant adaptables à l’ajout de critères supplémentaires. Ce travail présente aussi une série de vingt scénarios permettant de couvrir une grande variété de conditions possibles pour permettre de caractériser la qualité des trajectoires planifiées pour un UAV à voilure fixe. Ce travail propose de combiner ces deux éléments pour constituer un environnement de test détaillé comme point de référence pour les futurs travaux sur la planification de trajectoires d’UAV à voilure fixe.

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Toward UAV Path Planning Problem Optimization Considering the Internet of Drones

Shirabayashi,

Ruiz

2023

IEEE Access

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The use of Unmanned Aerial Vehicles (UAVs) has become popular in recent years, especially for their potential in various practical applications, but for their use to become a reality this context, it is necessary to study about it. One of the main problems involving UAVs, regardless of the application to which it will be used, is path planning, which is crucial to ensure safety, economy, and effectiveness. In this study we present a literature review on the optimization problem path planning and the methods used to solve it. To this end, we seek to explore the existing papers in literature on this topic, identifying mathematical models, analyzing characteristics of the objective function, types of obstacles, number of UAVs considered, the nature of the solution adopted and deployments and integration in the Internet of Drones (IoD). A comparative analysis of the works analyzed was presented in the form of tables for each path planning technique considered. In addition, some advantages and safety of the methods were also listed. We furthermore present a set of open research challenges, high-level insights, and future research directions related to the UAV path planning problem in the context of IoD. This study contributes deeply with the advancement of state of art regarding the path planning strategies on the Internet of Drones since we provide a thorough analysis of characteristics of the mathematical models used in the UAV path planning problem reviewing papers published in relevant journals and conferences in the last 4 years (2018 to 2022), highlighting the advantages and disadvantages of each method as well as the possibilities of implementation and integration with IoD.INDEX TERMS Internet of drones, Optimization, Path Planning techniques, Unmanned Aerial Vehicles (UAV), IoD architecture. I. INTRODUCTIOND RONES, as known as Unmanned Aerial Vehicles (UAVs), is the most usual way to refer to an aircraft that does not carry a crew. Several terms are used to refer to "drones". Besides UAV, the most common are: unmanned aircraft systems (UAS), remotely piloted vehicles (RPVs), remotely piloted aircraft (RPAs). In recent years, we have observed the increasing popularity and use of UAVs, in different handy applications, such as delivery, transportation, agriculture, monitoring, medical assistance, image capturing, among others [1]-[9]. In the past, the UAVs were mainly used in military applications where one or more drones were used for weather monitoring, soldier recognition, search and rescue. These applications remain and as listed above, several others have emerged, bringing new challenges and the need for more research about them.Currently, there are several studies related to delivery applications with UAVs. Large and well-known companies such as Amazon [10], Google, iFood [11], are investing in research and possibilities to make their deliveries via drones. However, for such implementation to be possible and feasible in the future, it is necessary to organize and coordinate the airspace and drones, since se...

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Recent advances in unmanned aerial vehicles real-time trajectory planning

Cited by 12 publications

References 99 publications

An autonomous drone for search and rescue in forests using airborne optical sectioning

An autonomous drone for search and rescue in forests using airborne optical sectioning

Point de référence pour la planification de trajectoires d’UAV à voilure fixe

Toward UAV Path Planning Problem Optimization Considering the Internet of Drones

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