Controls and Control Theory Commons^™

A Convex Approach To Advanced Air Mobility Trajectory Optimization, Yufei Wu

Doctoral Dissertations

This dissertation addresses the challenge of real-time trajectory optimization for electric Vertical Take-Off and Landing (eVTOL) vehicles within the framework of Advanced Air Mobility (AAM). With urban airspaces becoming increasingly crowded, ensuring the safety, efficiency, and feasibility of eVTOL operations is crucial. This research primarily focuses on the development and application of convex optimization techniques to solve trajectory optimization problems that not only enhance operational capabilities but also ensure adherence to stringent safety and efficiency standards.

The study is structured into several critical analyses and methodological developments across multiple chapters. In the first chapter, I introduce a multi-phase trajectory optimization …

State Omniscience For Cooperative Local Catalog Maintenance Of Close Proximity Satellite Systems, Chris Hays

Doctoral Dissertations and Master's Theses

Resiliency in multi-agent system navigation is reliant on the inherent ability of the system to withstand, overcome, or recover from adverse conditions and disturbances. In large part, resiliency is achieved through reducing the impact of critical failure points to the success and/or performance of the system. In this view, decentralized multi-agent architectures have become an attractive solution for multi-agent navigation, but decentralized architectures place the burden of information acquisition directly on the agents themselves. In fact, the design of distributed estimators has been a growing interest to enable complex multi-sensor/multi-agent tasks. In such scenarios, it is important that each local …

On Uncertainty For Ill-Posed Robot Decision Problems, Jared Joseph Beard

Graduate Theses, Dissertations, and Problem Reports

As robots adopt more real world responsibilities, they will be expected to solve more complicated problems. In some cases limited prior knowledge will result in unmodelled environmental conditions; in others, multiple users may have competing perspectives on how to frame a decision problem. Many existing frameworks, namely Markov decision processes (MDP) presuppose users have identified a specific problem with models sufficient to solve or learn a problem. If we wish to extend MDPs to novel problems or those heavily dependent on user feedback, autonomous decision makers must be able to identify limitations in how a given problem is framed and …