Principal Investigator Srinivas Ravela
Project Website http://caos.mit.edu/
The Cooperative Autonomous Observing Systems (CAOS) research collaborative develops technology for dynamic data and model-driven observing systems using cooperating autonomous aircraft. Of particular interest in environmental and atmospheric applications are sampling missions for climate (such as cloud processes), weather (such as NWP), natural hazards (volcanic emissions) and ecology (animal tracking and identification).
(*) We show how small-scale Unmanned Aircraft Systems can be efficiently employed to study physical scales up to 100 kilometers and a few hours at very low cost. The technological advances of operating multiple aircraft autonomously can be applied to larger scale problems. However, the solutions developed here are useful in their own right. For example, UAS can be used to map the transport of hazardous material or to improve our models of small-scale phenomena (e.g., shallow cumuli) known to have substantial impact.
(*) esearch encompasses theory, methodology and experiment. It is interdisciplinary in nature, demanding practice in the fields of Aeronautics, Computer Vision, Robotics, Meteorology and Machine Learning.