Abstract:
This paper reports on work performed under a program of research and development to design a team of unmanned aerial vehicles to efficiently and accurately sample atmospheric data in an urban environment or an area with complex terrain. The gathered wind field data are used to initialize weather models, thereby increasing the accuracy of these models. To achieve program objectives, the micro-Swarm Environmental Sensing (µSENS) technology was developed. µSENS enables a swarm, of small unmanned aerial systems (sUAS) to efficiently collect atmospheric data at high spatial and temporal resolution to assimilate with weather prediction tools. A swarm of intelligent sUAS equipped with wind and atmospheric sensors is deployed into an urban environment and collects atmospheric data at so-called information-rich locations. The data that are transmitted to the base station and used to initialize or update the weather prediction tools. µSENS includes compact sUAS vehicles designed specifically for atmospheric sampling, novel wind sensors, intelligent swarm control algorithms, and a ground control station to allow a single operator to manage the swarm and data collection process. This paper presents some of the main components of µSENS and lays a scientific foundation for sampling strategies for data collection in urban settings. Autonomous behaviors are described and the system is demonstrated through simulation and flight tests.