Intelligent Decentralized Unmanned Aerial Survey of Volcanic Plumes

Abstract

Many fields of Earth Science, including Volcanology, would greatly benefit from the ability of aerial platforms to provide coordinated high-density in situ sensor measurements near active and often dangerous physical phenomena, but the limitations of current autonomy limits the practical applicability and potential benefits of these platforms. Particularly, autonomous platforms lack the ability the ability to sense, predict, and respond to the phenomena and surrounding environments, which are often large-scale, hazardous, complex, and uncertain. In this paper we present an intelligent automated system for coordinating in situ measurements from multiple unmanned aerial vehicles to study emission, transport, composition, and in situ properties of aerosol emissions from active volcano sources. We present the hardware and software architectures that underlie NASA’s swarming Dragon Eye UAS platforms, describe model based approach for modeling and predicting environmental conditions around the Turrialba volcano, describe a decentralized control approach for coordination of multiple vehicles, and present the high-fidelity simulation environment developed to evaluate this system. We present results from simulation and from initial flight test validations. These results suggest that onboard model-based autonomy with the decentralized control architecture presented will enable these vehicles to autonomously and reliably gather in situ data in conditions that were previously inaccessible to unmanned systems. Finally, this paper describes the current status of this project and research, and describes the future direction planned for this research.