Multi-UAV Collaboration to Survey Tibetan Antelopes in Hoh Xil

Abstract

Reducing the total mission time is essential in wildlife surveys owing to the dynamic movement of animals throughout their migrating environment and potentially extreme changes in weather. This paper proposed a multi-UAV path planning method for counting various flora and fauna populations, which can fully use the UAVs’ limited flight time to cover large areas. Unlike the current complete coverage path planning methods, based on sweep and polygon, our work encoded the path planning problem as the satisfiability modulo theory using a one-hot encoding scheme. Each instance generated a set of feasible paths at each iteration and recovered the set of shortest paths after sufficient time. We also flexibly optimized the paths based on the number of UAVs, endurance and camera parameters. We implemented the planning algorithm with four UAVs to conduct multiple photographic aerial wildlife surveys in areas around Zonag Lake, the birthplace of Tibetan antelope. Over 6 square kilometers was surveyed in about 2 h. In contrast, previous human-piloted single-drone surveys of the same area required over 4 days to complete. A generic few-shot detector that can perform effective counting without training on the target object is utilized in this paper, which can achieve an accuracy of over 97%.

Complexity-Driven Trust Dynamics in Human–Robot Interactions: Insights from AI-Enhanced Collaborative Engagements

“…Further, trust in robots influences the application and execution of AI dynamic trust calibration mechanisms in high-risk military decision-making [25]. Even in ecological research, such as high-altitude animal migration studies, the validity of findings hinges on the level of trust in the HRI [26]. A noteworthy caveat, however, is that increasing decisional complexities can erode this trust, potentially undermining interaction [27].…”

The use of unmanned aerial vehicles for wildlife research

“…Wildlife surveys are essential to understand the dynamics, population status and response to climate variability (Hodgson et al, 2017). Drones are used to conduct censuses of populations in a more efficient way, since it is possible to reach places of difficult access, you can locate individuals that would not be located from the ground, either because they are behind obstacles such as rocks, or in difficult sites to observe from the ground (Ezat et al, 2018;Butcher et al, 2019;Colefax et al, 2019;Kelaher et al, 2019;Aota et al, 2021;Barreto et al, 2021;Francis et al, 2022;Huang et al, 2022). Some examples of the use of drones in wildlife monitoring are the following studies:…”