Understanding and forecasting weather is critical to nearly every industry and is even more important as weather patterns continue to change from their historical norms. Unmanned Aerial Systems (UASs) are capable of collecting valuable data in the lower kilometer of the atmosphere, which is under-sampled by traditional atmospheric sensing systems. However, a single UAS can only collect information from a small slice of the atmosphere at a time. This project will develop the systems and techniques to enable a UASs to carry, deploy, and recover smaller UASs and parachute-based weather sensors to create snapshots across atmospheric airmass boundaries. This will lead to the characterization of a much larger region of the lower atmosphere, consequently improving the understanding and forecasting of the weather. Carrying, deploying, and particularly recovering the systems, are critical to allow operations in remote locations and reuse of expensive sensors. Achieving these objectives requires new techniques to enable rich mid-air interactions between aerial robots. These techniques span from sensing and planning to control and run-time verification, all working together for the effective, efficient, and safe deployment of such teams of aerial robots. While this work is developed in the context of atmospheric sciences, the techniques are broadly applicable to many problems in distributed and collaborative robotics.
This project will contribute techniques and systems to enable the development and deployment of teams of UASs that perform mid-air capture and release of other systems. More specifically, the expected outcomes of this work include: 1) Sensing, planning and control methodologies for UASs intercepting airborne targets that have stochastic full six degree of freedom motion, 2) Foundational elements for matched maneuvers between heterogeneous classes of aerial robots to perform aerial docking, 3) Strategies for rapid aerial deployment-capture-redeployment cycles for teams of UASs to enable observations over large geographic scales, 4) Run-time inference and enforcement of protocols orchestrating the interactions between distributed, heterogeneous robotic systems, and 5) Improved atmospheric sensing and monitoring capabilities that will enhance understanding and forecasting of atmospheric phenomena.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
