# Wildlife Monitoring Using a Multi-UAV System with Optimal Transport Theory
###### Abstract  
This paper addresses a wildlife monitoring problem using a team of unmanned aerial vehicles (UAVs) with the optimal transport theory. The state-of-the-art technology using UAVs has been an increasingly popular tool to monitor wildlife compared to the traditional methods such as satellite imagery-based sensing or GPS trackers. However, there still exist unsolved problems as to how the UAVs need to cover a spacious domain to detect animals as many as possible. In this paper, we propose the optimal transport-based wildlife monitoring strategy for a multi-UAV system, to prioritize monitoring areas while incorporating complementary information such as GPS trackers and satellite-based sensing. Through the proposed scheme, the UAVs can explore the large-size domain effectively and collaboratively with a given priority. The time-varying nature of wildlife due to their movements is modeled as a stochastic process, which is included in the proposed work to reflect the spatio-temporal evolution of their position estimation. In this way, the proposed monitoring plan can lead to wildlife monitoring with a high detection rate. Various simulation results including statistical data are provided to validate the proposed work. In all different simulations, it is shown that the proposed scheme significantly outperforms other UAV-based wildlife monitoring strategies in terms of the target detection rate up to 3.6 times. U  
A 2021 23 April 2021 29 April 2021  
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**2021** **202  
lot of human efforts. In [6], the total cost of activities to capture animals, deploy GPS collars, and analyze data are more than $300,000 in a year only in the state of Colorado, USA. Also, the GPS trackers used to track the animals have some drawbacks such as intermittent GPS data transmission due to the limited energy of the device, unavailability of the GPS tracker depending on their locations, and partial information without details (e.g., population size, age and gender ratios, foraging strategies, etc.). Other technologies to monitor wildlife include camera traps [7; 8], acoustic recording devices [9; 10], environmental DNA monitoring for tracking community composition [11; 12], and genetic monitoring for identifying individuals within populations [13]. These methods alone are not effective as they cannot cover a wide range and the installation of sensors requires some preliminary data to choose proper locations. Thus, there have been attempts to utilize the new technology using unmanned aerial vehicles (UAVs), or equivalently drones, in order to efficiently gather more detailed data with less time and cost [14; 15; 16; 17]. In general, UAVs are referred to as aircraft piloted by remote control or embedded computer programs without human onboard as broadly defined in [18; 19]. It has been reported that UAV-based sensing is an increasingly popular and promising conservation tool in ecological monitoring [20; 21; 22]. The data from UAVs can provide useful information for timely management responses [23]. The UAVs can be deployed quicker than manned airplanes [24] and are known to be less sensitive to ground survey techniques for wildlife monitoring [25]. As a consequence, many researchers and ecologists applied the UAV technologies to supplementing the conventional techniques for monitoring, conservation, and management practices [26; 27; 25]. Despite many advantages of UAV-based monitoring, detecting animal herds using UAVs is still a challenging problem due to the large domain size, limited energy of UAVs, and wildlife movements. Further, no systematized approaches have been developed in efforts to incorporate other complementary monitoring tools (e.g., GPS trackers) in the UAV-based monitoring. To tackle the above problem, this paper investigates a new wildlife monitoring scheme using a multi-UAV system.