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Finding Survivors in a Terrestrial Region: A Solution to the Unmanned Aerial Vehicle Trajectory Planning Problem
Unmanned Aerial Vehicles (UAVs) are often employed for a wide range of tasks such as military, reconnais-sance, commercial, agriculture, disaster management, product delivery, research, etc. Among these, drones are crucial during a disaster since they must assess the damage and quickly locate the su...
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Main Authors: | , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Unmanned Aerial Vehicles (UAVs) are often employed for a wide range of tasks such as military, reconnais-sance, commercial, agriculture, disaster management, product delivery, research, etc. Among these, drones are crucial during a disaster since they must assess the damage and quickly locate the survivors under the rubble. Drones fly autonomously or operated by remote pilots. In autonomous drones, trajectories are programmed to identify the survivors in a given coverage area. This is mapped to a trajectory planning problem for complete coverage with minimal time and minimal energy. In this paper, we propose a novel two-stage algorithm for finding survivors in a terrestrial region. In the first stage, an efficient waypoint generation algorithm for locating the waypoints is designed and in the second stage, a column-by-column traversal algorithm is designed to effectively traverse the generated waypoints. The experiments are conducted in real time using Tello drones. From the experiments, it is inferred that our waypoint generation algorithm results in a lower number of waypoints than the other existing techniques. Our traversal algorithm is as efficient as the existing spiral algorithm. |
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ISSN: | 2155-2509 |
DOI: | 10.1109/COMSNETS56262.2023.10041346 |