ISEP/INESC TEC Aerial Robotics Team for Search and Rescue Operations at the EuRathlon Challenge 2015

Sousa, Pedro; Ferreira, António; Moreira, M.; Santos, Tiago C. dos; Martins, Alfredo; Dias, André; Almeida, J.; Silva, Eduardo

doi:10.1109/icarsc.2016.49

Cited by 6 publications

(5 citation statements)

References 11 publications

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“…Furthermore, they have won the Grand Challenge of two international competitions of search and rescue missions using the UAVs OTUS and STORK: the euRathlon 7 [8] and ERL Emergency Robots 8 , in 2015 and 2017, respectively.…”

Section: Motivationmentioning

confidence: 99%

“…Given the numerous UAVs with multiple sensors, motors and design configurations, they present applicability in several kinds of operations, such as search and rescue operations [8,9], delivery [10], surveillance [11], inspection and interaction with the environment [12,13]. Considering the applications scenarios, there are missions where the UAV must fly in civilian airspace, i.e., they must fly over populated areas.…”

Section: Introductionmentioning

confidence: 99%

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Emergency Landing Spot Detection for Unmanned Aerial Vehicle

Loureiro

Soares

Dias

et al. 2019

Advances in Intelligent Systems and Computing

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Primeiro, gostaria de agradecer ao meu orientador, Eng. André Dias, pelo desafio proposto, como também pelo auxílio durante o desenvolvimento desta dissertação.Gostaria de agradecer também os meus colegas de mestrado que fizeram parte deste percurso.Aos meus amigos de longa data pela amizade durante esses anos. Mesmo que indiretamente, tiveram grande contribuição para a conclusão deste mestrado.Ao meu irmão, Bruno Loureiro, pelo carinho e preocupação demonstrado ao longo desses anos. O teu apoio foi fundamental para o fim desta etapa.Por fim, um agradecimento especial aos meus pais, Fernando e Nazaré. Obrigado pelo vosso carinho, vossa paciência e cuidado durante toda a minha vida. Serei eternamente grato por todos esforços e desafios superados para poderem me proporcionar todas estas oportunidades. Espero poder retribuir tudo o que já fizeram por mim.Muito obrigado.

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Section: Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Emergency Landing Spot Detection for Unmanned Aerial Vehicle

Loureiro

Soares

Dias

et al. 2019

Advances in Intelligent Systems and Computing

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“…Concerning the UAV classification, there are several ways in which UAVs can be defined: aerodynamics, landing, weight, and range [3]. Considering the state of the art of UAVs, commercial or research, there is a large spectrum of applications, such as search-and-rescue operations [4,5], delivery, surveillance, inspection, and interaction with the environment [6,7].…”

Section: Introductionmentioning

confidence: 99%

Emergency Landing Spot Detection Algorithm for Unmanned Aerial Vehicles

Loureiro¹,

Dias

Martins

et al. 2021

Remote Sensing

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The use and research of Unmanned Aerial Vehicle (UAV) have been increasing over the years due to the applicability in several operations such as search and rescue, delivery, surveillance, and others. Considering the increased presence of these vehicles in the airspace, it becomes necessary to reflect on the safety issues or failures that the UAVs may have and the appropriate action. Moreover, in many missions, the vehicle will not return to its original location. If it fails to arrive at the landing spot, it needs to have the onboard capability to estimate the best area to safely land. This paper addresses the scenario of detecting a safe landing spot during operation. The algorithm classifies the incoming Light Detection and Ranging (LiDAR) data and store the location of suitable areas. The developed method analyses geometric features on point cloud data and detects potential right spots. The algorithm uses the Principal Component Analysis (PCA) to find planes in point cloud clusters. The areas that have a slope less than a threshold are considered potential landing spots. These spots are evaluated regarding ground and vehicle conditions such as the distance to the UAV, the presence of obstacles, the area’s roughness, and the spot’s slope. Finally, the output of the algorithm is the optimum spot to land and can vary during operation. The proposed approach evaluates the algorithm in simulated scenarios and an experimental dataset presenting suitability to be applied in real-time operations.

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“…Additionally, it is advantageous if the system is fitted with a communications module capable of reaching a central control station [7]. Agriculture [1,8], first-aid response [9][10][11], surveying and photogrammetry [12,13] or strategic positioning for unscheduled monitoring [14][15][16][17] are examples of applications that can benefit from autonomous remote operations. In extensive agriculture fields, one or more landing bases can be placed in optimal locations allowing periodic surveying for monitoring the crops' growth and health [18].…”

Section: Introductionmentioning

confidence: 99%

Precision Landing for Low-Maintenance Remote Operations with UAVs

Moreira¹,

Azevedo

Ferreira³

et al. 2021

Drones

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This work proposes a fully integrated ecosystem composed of three main components with a complex goal: to implement an autonomous system with a UAV requiring little to no maintenance and capable of flying autonomously. For this goal, was developed an autonomous UAV, an online platform capable of its management and a landing platform to enclose and charge the UAV after flights. Furthermore, a precision landing algorithm ensures no need for human intervention for long-term operations.

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ISEP/INESC TEC Aerial Robotics Team for Search and Rescue Operations at the EuRathlon Challenge 2015

Cited by 6 publications

References 11 publications

Emergency Landing Spot Detection for Unmanned Aerial Vehicle

Emergency Landing Spot Detection for Unmanned Aerial Vehicle

Emergency Landing Spot Detection Algorithm for Unmanned Aerial Vehicles

Precision Landing for Low-Maintenance Remote Operations with UAVs

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