The Use of UAV's for Search and Rescue Operations

Półka, Marzena; Ptak, Szymon; Kuziora, Łukasz

doi:10.1016/j.proeng.2017.06.129

Cited by 94 publications

(47 citation statements)

References 6 publications

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“…The significant impact of the unmanned aerial vehicles (UAVs) in various robotics fields made them a promising solution for urban search and rescue tasks. For victim detection, the UAV could utilize the onboard sensors and the onboard intelligence to accurately detect and locate victims in disaster scenes in order to increase the likelihood of finding victims [18][19][20]. For mapping and 3D reconstruction, the UAV should be capable of reconstructing the scene in 3D and locating the contextual and rich information that can be used by the rescuers' team.…”

Section: Related Workmentioning

confidence: 99%

Exploration for Object Mapping Guided by Environmental Semantics using UAVs

Ashour

Taha²,

Dias

et al. 2020

Remote Sensing

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This paper presents a strategy to autonomously explore unknown indoor environments, focusing on 3D mapping of the environment and performing grid level semantic labeling to identify all available objects. Unlike conventional exploration techniques that utilize geometric heuristics and information gain theory on an occupancy grid map, the work presented in this paper considers semantic information, such as the class of objects, in order to gear the exploration towards environmental segmentation and object labeling. The proposed approach utilizes deep learning to map 2D semantically segmented images into 3D semantic point clouds that encapsulate both occupancy and semantic annotations. A next-best-view exploration algorithm is employed to iteratively explore and label all the objects in the environment using a novel utility function that balances exploration and semantic object labeling. The proposed strategy was evaluated in a realistically simulated indoor environment, and results were benchmarked against other exploration strategies.

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Section: Related Workmentioning

confidence: 99%

Exploration for Object Mapping Guided by Environmental Semantics using UAVs

Ashour

Taha²,

Dias

et al. 2020

Remote Sensing

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“…This is due to emerging medical problems in affected people [4,5]. Although the activities of rescue services have a long history [6], modern information technologies and new vehicles give hope for a more successful solution of the task.…”

Section: The Relevance Of the Taskmentioning

confidence: 99%

“…UAVs, as a rule, are cheaper and more universal than traditional methods of remote sensing, and therefore they can be considered as a good alternative for obtaining images and other physical parameters before, during and after a natural disaster [11]. For the task of saving people, the combination of the efforts of ground rescue services and UAVs is especially relevant [6]. A specific implementation for finding people in the mountains shows the advantages of such a concept [12].…”

Section: Uav Application Conceptsmentioning

confidence: 99%

The Use of UAVs to Save People in the Mountains: Tasks, Problems, Perspective

Romanova

2020

ITM Web Conf.

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The actual problem of organizing and conducting rescue operations in the mountains is considered. The achievements associated with the following factors were noted: the active development of UAVs of various designs, masses, and equipment; development of new information systems, including sensors, communication systems; the emergence of new image processing algorithms and other types of data based on artificial intelligence methods. It was emphasized that a fundamentally new achievement that opens up broad prospects is an integrated approach to the use of rescue equipment, including ground-based mobile equipment, UAVs of various types, global navigation and mobile communications, and professional rescuers. Problems were identified that are associated with the difficulties of the task, including a complex mountainous terrain, snow cover, avalanches, strong winds, low temperatures, immobility and even lack of communication with the victims. The article considers the problem of low temperatures, which leads to icing, which gives rise to an uncontrolled change in the properties of the control object UAVs, difficulties in the functioning of control elements, and distortion of the sensors. Based on the methods of artificial intelligence, including modern methods of detecting damage, a comparative analysis of different approaches was carried out and a predominant approach was drawn, which allows a high degree of certainty to detect problems of UAV icing and timely change of control system settings.

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“…Large-scale Unmanned Aerial Vehicle (UAV) [1] has good performance in terms of mobility and maneuverability under the complex environment. As the development of the smart devices and the algorithm, large-scale UAV is widely used in various fields, such as search and rescue [2], coastal monitoring [3], surveillance system [4], and so on. As the key technology of the large-scale UAV, path planning algorithm has recently gained great attention in the study of aerospace control community.…”

Section: Introductionmentioning

confidence: 99%

Bi-Directional Adaptive A* Algorithm Toward Optimal Path Planning for Large-Scale UAV Under Multi-Constraints

Zhen

et al. 2020

IEEE Access

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For large-scale Unmanned Aerial Vehicle (UAV), it is a challenging problem to automatically generate an optimal path considering the multi-constraints. In order to improve the efficiency and optimality of conventional A * algorithm, Bi-directional adaptive A * algorithm is proposed in this paper. Regarding to the defect of expansion efficiency for conventional A * algorithm based on multi-direction, directional search strategy is adopted to improve the efficiency of expansion process and guarantee the smooth of the path. Adaptive step strategy and adaptive weight strategy are used to improve the exploration speed and the accuracy of the proposed algorithm. By adopting bi-directional search strategy, the exploration ability of the algorithm can be improved in some complex environment. Finally, rewiring process is introduced to optimize the path length. The simulation for UAV path planning under the multi-constraints conditions is carried out and the simulation results show that Bi-directional adaptive A * algorithm has the superiority in run time and path quality. INDEX TERMS A * algorithm, adaptive strategy, unmanned aerial vehicle, path planning.

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The Use of UAV's for Search and Rescue Operations

Cited by 94 publications

References 6 publications

Exploration for Object Mapping Guided by Environmental Semantics using UAVs

Exploration for Object Mapping Guided by Environmental Semantics using UAVs

The Use of UAVs to Save People in the Mountains: Tasks, Problems, Perspective

Bi-Directional Adaptive A* Algorithm Toward Optimal Path Planning for Large-Scale UAV Under Multi-Constraints

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