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Autonomous survey and aerial photogrammetry applications require solving a path planning problem that ensures sensor coverage over a specified area. In this work, we provide a multi-robot path planning method that can obtain this coverage over an arbitrary area of interest. We extend our previous method, path optimization for population counting with overhead robotic networks (POPCORN), by a divide-and-conquer scheme, split and link tiles (SALT), which drastically decreases the time needed for route planning. These POPCORN instances can be computed in parallel and combined with SALT in a scalable manner to produce coverage paths over very large areas of interest. To demonstrate this algorithm’s capabilities, we implemented our planning algorithm with a team of drones to conduct multiple photographic aerial wildlife surveys of the Cape Crozier Adélie penguin rookery on Ross Island, Antarctica, one of the largest Adélie penguin colonies in the world. The colony, which contains over 300,000 nesting pairs and spans over 2 km, was surveyed in about 3 hours. In contrast, previous human-piloted single-drone surveys of the same colony required over 2 days to complete. We also have deployed our survey system at several islets at Mono Lake, California, to survey a California gull colony as well as at a 2000-acre ranch in Marin, California. We provide this survey path planning tool as an open-source software package named wadl. 

Speed is essential in wildlife surveys due to the dynamic movement of animals throughout their environment and potentially extreme changes in weather. In this work, we present a multirobot path-planning method for conducting aerial surveys over large areas designed to make the best use of limited flight time. Unlike current survey path-planning solutions based on geometric patterns or integer programs, we solve a series of satisfiability modulo theory instances of increasing complexity. Each instance yields a set of feasible paths at each iteration and recovers the set of shortest paths after sufficient time. We implemented our planning algorithm with a team of drones to conduct multiple photographic aerial wildlife surveys of Cape Crozier, one of the largest Adélie penguin colonies in the world containing more than 300,000 nesting pairs. Over 2 square kilometers was surveyed in about 3 hours. In contrast, previous human-piloted single-drone surveys of the same colony required over 2 days to complete. Our method reduces survey time by limiting redundant travel while also allowing for safe recall of the drones at any time during the survey. Our approach can be applied to other domains, such as wildfire surveys in high-risk weather conditions or disaster response.