SBIR Phase I: A Universal Flight Management Unit for Unmanned Aircraft Systems

这项小企业创新研究（SBIR）项目的更广泛影响/商业潜力是实现安全可靠的自主无人飞行操作。无人机系统（UAS）用于越来越多需要提高车辆自主性的应用，例如室内操作，民用基础设施检查，精准农业和水产养殖，遥感，野生动物跟踪和保护以及包裹/药品交付。随着自主无人机应用的多样性和数量的不断增长，独立于平台的机载自主解决方案变得越来越重要。拟议技术的潜在细分市场集中在最具挑战性的用例上，如最后一英里交付、城市基础设施检查和客运航空工具（空中救护车、空中出租车、空中班车）。因此，与平台无关的机载自主性的技术进步，特别是对于小型无人机系统（sUAS）来说，可以通过实现UAS的安全性和可靠性，对社会产生巨大的积极影响。这个小型企业创新研究（SBIR）第一阶段项目以平台无关的方式研究了一个通用飞行管理单元（FMU），用于UAS的非线性稳定和鲁棒自治。目前，缺乏非线性稳定和鲁棒的飞行堆栈，这些飞行堆栈是平台/模型无关的，并且可以在现有硬件上实时实现，特别是对于sUAS。要实现无人机可靠的平台独立自主性，需要克服的两个关键挑战是：(A)在机载处理器、传感器和执行器存在约束条件下的动态稳定性；(B)对动态外部不确定性（如风、天气）和内部原因（如有效载荷变化、机载故障）的鲁棒性。第一阶段研究的科学目标是：(1)无人机自主操作的机载轨迹规划、控制和导航，以提供动态稳定性和对干扰和传感器噪声的鲁棒性；(2)将制导、导航和控制算法与商用硬件进行嵌入式软硬件集成，构建用于机载自治的FMU；(3)在不同四旋翼无人机平台（包括飞翼平台）上进行实验验证和验证。这种平台无关的FMU背后的底层框架将是非线性稳定和鲁棒的无模型控制和估计技术，以确保安全可靠的自主操作。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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to enable safe and reliable autonomous unmanned flight operations. Unmanned aircraft systems (UAS) are used in a growing number of applications requiring increased vehicle autonomy, such as indoor operations, civilian infrastructure inspection, precision agriculture and aquaculture, remote sensing, wildlife tracking and conservation, and package/medicine delivery. As the diversity and number of applications of autonomous UAS keep growing, platform-independent solutions to onboard autonomy become increasingly important. Potential market segments for the proposed technology are focused on the most challenging use cases such as last-mile delivery, urban infrastructure inspection, and passenger air vehicles (air ambulance, air taxi, air shuttle). Therefore, technological advances in platform-independent onboard autonomy, particularly for small unmanned aircraft systems (sUAS), can have a large positive societal impact by enabling safety and reliability of UAS. This Small Business Innovation Research (SBIR) Phase I project investigates a universal flight management unit (FMU) for nonlinearly stable and robust autonomy of UAS, in a platform-independent manner. At present, there is a dearth of nonlinearly stable and robust flight stacks that are platform/model-independent and real-time implementable on existing hardware, particularly for sUAS. Two critical challenges to be overcome for reliable platform-independent autonomy of UAS are: (A) dynamic stability in the presence of constraints on onboard processors, sensors and actuators; and (B) robustness to dynamic external uncertainties (e.g., wind, weather) and internal causes (e.g., changing payloads, onboard faults). The scientific objectives of this Phase 1 research are: (1) onboard trajectory planning, control and navigation for autonomous operations of UAS to provide dynamic stability and robustness to disturbances and sensor noise; (2) embedded software-hardware integration of guidance, navigation and control algorithms with commercially available hardware to build a FMU for onboard autonomy; and (3) experimental verification and validation of this FMU on different quadrotor unmanned aerial vehicle platforms, including a flying-wing platform. The underlying framework behind this platform-independent FMU will be nonlinearly stable and robust model-free control and estimation techniques that ensure safe and reliable autonomous operations.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.