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Now that the EA-DDDAS framework has been put through the paces, we're planning two days of flight testing that allow the system operate fully autonomously. This means that the high-level planner and trajectory optimization layer will be left to

We've flown a full system test with data flow originating from the dual-doppler radar synthesis, feeding the energy-aware path planner resulting in plans sent accordingly to the PixHawk autopilot on-board the Tempest aircraft. Several different

Sorry for the lack of updates, things have been very busy here in Lubbock. We've run into a bunch of unforseen challenges along the way, but it wouldn't be an engineering field deployment if everything went perfectly the first time! Since our first

The EA-DDDAS systems are being tested and steadily coming online. We successfully received Ka-doppler data, advanced the wind field through an online forecast system, and recorded the wind field to a MongoDB system operating in the field. This

RECUV has received permission from the Federal Aviation Administration to start flying the Tempest UAS over parts of Texas and Oklahoma this spring in the heart of Tornado Alley to conduct weather research. The new “southern COA”

During the EA-DDDAS deployment this summer we'll be flying a Tempest with a PixHawk autopilot on-board. The PixHawk uses the well-known MAVLink protocol released by Lorenz Meier over at ETH Zürich. The protocol was designed to be language

The Trajectory Optimization Layer (TOL) is a middleware component of the EA-DDDAS aircraft control system. It resides below the extended time-horizon path planner and above the aircraft path following controller. It's primary responsibility is

This is where we will be providing the latest news and updates on our EA-DDDAS field deployments this June in Lubbock, TX. Check back closer to June for news!