Synergistic perception and control simplex for verifiable safe vertical landing
Zhao, Yang
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https://hdl.handle.net/2142/124610
Description
Title
Synergistic perception and control simplex for verifiable safe vertical landing
Author(s)
Zhao, Yang
Issue Date
2024-05-02
Director of Research (if dissertation) or Advisor (if thesis)
Hovakimyan, Naira
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Vertical Take-off And Landing
Air Taxi
Adaptive Control
Safe Driving Framework
Language
eng
Abstract
Autonomous driving systems play an essential role in modern robotic systems. However, advanced machine learning-based perception and control algorithms may fail to avoid collisions occasionally. In this thesis, we integrate and evaluate a holistic safety driving system. Our work and evaluation mainly focus on an air taxi system, a prospective future commute tool that will significantly enhance efficiency and air mobility. The innovative safety driving framework contains verifiable algorithms. We adopt the Perception Simplex system for reliable obstacle detection to avoid collisions. In addition, we integrate L1 adaptive control to improve the system’s robustness. To further reduce the landing time and enhance efficiency, we update the safety envelope by considering real-time dynamic confirmation of the control capability instead of the static worst-case control capability. This work demonstrates the success and reliability of the safety driving framework, which can significantly improve landing efficiency while ensuring safety and robustness. This framework can also be integrated into other autonomous systems to improve safety in many fields further.
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