A novel metric for detecting quadrotor loss-of-control

• Published in: arXiv.org
• Main Authors: Jasper van Beers, Solanki, Prashant, de Visser, Coen
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 12.08.2024
• Subjects: Actuators; Computer Science - Robotics; Computer Science - Systems and Control; Explicit knowledge; Fault detection; Industrial development; Rotary wing aircraft; Unmanned aerial vehicles; Unmanned helicopters; Yaw
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2408.06025

Unmanned aerial vehicles (UAVs) are becoming an integral part of both industry and society. In particular, the quadrotor is now invaluable across a plethora of fields and recent developments, such as the inclusion of aerial manipulators, only extends their versatility. As UAVs become more widespread, preventing loss-of-control (LOC) is an ever growing concern. Unfortunately, LOC is not clearly defined for quadrotors, or indeed, many other autonomous systems. Moreover, any existing definitions are often incomplete and restrictive. A novel metric, based on actuator capabilities, is introduced to detect LOC in quadrotors. The potential of this metric for LOC detection is demonstrated through both simulated and real quadrotor flight data. It is able to detect LOC induced by actuator faults without explicit knowledge of the occurrence and nature of the failure. The proposed metric is also sensitive enough to detect LOC in more nuanced cases, where the quadrotor remains undamaged but nevertheless losses control through an aggressive yawing manoeuvre. As the metric depends only on system and actuator models, it is sufficiently general to be applied to other systems.