NRI: INT: COLLAB: Raining Drones: Mid-Air Release & Recovery of Atmospheric Sensing Systems

了解和预测天气对几乎所有行业都至关重要，随着天气模式不断从历史常态变化，这一点变得更加重要。无人机系统（UASs）能够在低千米的大气中收集有价值的数据，这是传统大气传感系统采样不足的。然而，单个无人机一次只能从一小片大气中收集信息。该项目将开发系统和技术，使无人机能够携带、部署和回收更小的无人机和基于降落伞的天气传感器，以创建跨越大气气团边界的快照。这将导致对低层大气更大区域的描述，从而提高对天气的理解和预报。携带、部署，特别是回收系统，对于实现远程操作和重复使用昂贵的传感器至关重要。实现这些目标需要新的技术来实现空中机器人之间丰富的空中交互。这些技术涵盖了从传感和规划到控制和运行时验证，所有这些技术都是为了有效、高效和安全地部署这些空中机器人团队而共同努力的。虽然这项工作是在大气科学的背景下发展起来的，但这些技术广泛适用于分布式和协作机器人中的许多问题。该项目将提供技术和系统，以开发和部署执行空中捕获和释放其他系统的无人机团队。更具体地说，这项工作的预期成果包括：1)无人机拦截具有随机全六自由度运动的空中目标的传感、规划和控制方法；2)异构类空中机器人之间匹配机动以执行空中对接的基本要素；3)无人机团队快速空中部署-捕获-再部署周期策略，以实现大地理尺度上的观测。4)运行时推断和执行协调分布式、异构机器人系统之间交互的协议；5)改进的大气传感和监测能力，将增强对大气现象的理解和预测。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.