Abstract
Activities on Unmanned Aerial Vehicle (UAV) have increased over the last years and there are many fields in which UAVs can be used. One of the basic applications is reconnaissance of a given area using multiple UAVs. To perform reconnaissance mission, there are two methods: (i) path planning to navigate the pre-determined route; and (ii) random mobility method to explore without prior knowledge. In this paper, we indicate the imbalance problem of existing random mobility models for reconnaissance and propose a new model considering reconnaissance balance based on the number of visits. We divide the scanning area into N zones and then select a zone stochastically in which the search is insufficient. We evaluated the performance of the model by focusing on the coverage rate and average inter-visiting time. The proposed model shows that the 90%-coverage reaching time is improved by about 25% and the average inter-visiting time is improved by up to 15% compared to the previous approach.
Highlights
As computing and communication technologies have developed rapidly, Unmanned Aerial Vehicle (UAV) (UnmannedAerial Vehicles) have received much attention in research fields, and in real-life applications including forest fire monitoring [1], highway traffic monitoring [2], etc
We focus on the random mobility method to enhance the reconnaissance performance
The 90%-coverage reaching time of the Pheromone Repel model takes 4208 s and the proposed model takes 3122 s, which means the proposed model has a performance improvement of about 25% compared to the Pheromone
Summary
As computing and communication technologies have developed rapidly, UAVs (Unmanned. Aerial Vehicles) have received much attention in research fields, and in real-life applications including forest fire monitoring [1], highway traffic monitoring [2], etc. The random mobility method has no pre-planned paths for UAVs’ movements. Each UAV decides its reconnaissance path dynamically based on random mobility models [3,4,9,10,11,13,14,15,16]. This random mobility method can overcome unexpected events, such as UAV failure, and provides unpredictability of reconnaissance to targets. Pheromone Repel model [9] shows high reconnaissance rate in a specific area because UAVs fly based on the shared information.
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