Generalized trajectory modeling and prediction for unmanned aircraft systems low-altitude small unmanned aircraft system (suas) operations offer exciting new flight opportunities but also pose a…

The University of Michigan was awarded a $999,152 cooperative agreement from the National Aeronautics and Space Administration (NASA) to develop generalized trajectory modeling and prediction capabilities for small unmanned aircraft systems (UAS) operations in low-altitude airspace. This effort supports NASA's UAS Traffic Management (UTM) system, which aims to enable safe and coordinated flight of various UAS platforms. The project will focus on translating performance envelopes of fixed-wing, multicopter, and hybrid UAS into models and data structures for trajectory planning and prediction, accounting for nominal and hazardous atmospheric conditions as well as potential vehicle failures. The goal is to produce reusable templates for UAS trajectory modeling, prediction, and validation to support emerging low-altitude UAS missions. This contract award is not designated as a set-aside.

Generalized trajectory modeling and prediction for unmanned aircraft systems low-altitude small unmanned aircraft system (suas) operations offer exciting new flight opportunities but also pose a number of safety challenges related to the low-altitude environment, diversity of platforms, and potential for failures given low-cost suas with limited redundancy. NASA has proposed a UAS traffic management (UTM) system to support low-altitude suas flight operations. UTM will allow suas of all types to communicate and coordinate flight plans. To achieve appropriate levels of safety and coordination, UTM must be able to model, predict, and validate suas flight trajectories. This proposal is directly responsive to subtopic 2.6 of nasas safe autonomous systems operations (saso) project. Fixed-wing, multicopter, and hybrid suas performance envelopes will be translated to models and compact data structures for a diverse suite of trajectory primitives and full flight plans capable of supporting emerging low-altitude missions. Low-altitude nominal and hazardous atmospheric models will be developed and applied to produce realistic suas aeromechanics models at high-fidelity and reducedorder. Efforts will focus on hazards and failures with potential to challenge existing trajectory modeling and prediction methods, including suas case studies over critical failure scenarios, optimal gliding and soaring, and multi-vehicle teams. Focus will be placed on development and testing of UTM-centered data structures and trajectory modeling and prediction methods. Validation will be emphasized in all work through theoretical analysis, simulation, and flight testing. This project will develop techniques to characterize, validate, and specify reusable templates for low-altitude suas trajectory modeling, predictionm and validation. The university of michigan investigator team offers collective expertise covering all subtopic 2.6 research areas and will directly address each of the six proposed subtopic 2.6 research tasks. The team will perform an initial literature survey, then will build a family of suas vehicle and interface models and failure models. The team will characterize nominal and hazardous atmospheric boundary layer conditions, and will establish methods to formally predict the impact of environmental hazards and vehicle failures on flight trajectories. Modeling, prediction, and validation capabilities will be evaluated over a suite of metrics evaluating the efficiency, accuracy, and extensibility of proposed data structures, models, and algorithms. Results will be generalizable to the different suas classes, onboard automation capabilities, and mission types.