提出可自适应故障的四旋翼飞行系统,实现未知环境下的自主避障飞行。
Rotor-Failure-Aware Quadrotors Flight in Unknown Environments
- 融合故障检测与非线性模型预测控制,快速识别并稳定故障状态。
- 基于激光雷达与时空联合优化,规划安全飞行路径,支持复杂环境导航。
- 首次实现在杂乱房间和未知森林中的故障四旋翼自主飞行,适合无人机容错研究者。
四旋翼在发生旋翼故障时,因转子不平衡易引发高速旋转与振动,给未知环境中的自主飞行带来巨大挑战。现有主流方法依赖容错控制(FTC)和预设轨迹跟踪,但在线故障检测与诊断(FDD)、后故障轨迹规划及复杂未知环境下的协同控制尚未实现。本文提出一种旋翼故障感知的四旋翼导航系统,以减轻旋翼失衡影响。首先,设计一种结合电机动态的复合型FDD-非线性模型预测控制器(NMPC),实现快速故障检测与飞行稳定。其次,开发一种基于FDD结果与时空联合优化的故障感知规划器,并构建配备四个抗扭矩板的激光雷达平台,确保高速旋转下的可靠感知。最后,大量对比实验验证了该方法在旋翼卸载与电机停转等故障场景下的优越性能。实验首次证明,本方案可在包含障碍物房间和未知森林等复杂环境中实现故障四旋翼的自主飞行。
原文摘要 · Abstract (English)
Rotor failures in quadrotors may result in high-speed rotation and vibration due to rotor imbalance, which introduces significant challenges for autonomous flight in unknown environments. The mainstream approaches against rotor failures rely on fault-tolerant control (FTC) and predefined trajectory tracking. To the best of our knowledge, online failure detection and diagnosis (FDD), trajectory planning, and FTC of the post-failure quadrotors in unknown and complex environments have not yet been achieved. This paper presents a rotor-failure-aware quadrotor navigation system designed to mitigate the impacts of rotor imbalance. First, a composite FDD-based nonlinear model predictive controller (NMPC), incorporating motor dynamics, is designed to ensure fast failure detection and flight stability. Second, a rotor-failure-aware planner is designed to leverage FDD results and spatial-temporal joint optimization, while a LiDAR-based quadrotor platform with four anti-torque plates is designed to enable reliable perception under high-speed rotation. Lastly, extensive benchmarks against state-of-the-art methods highlight the superior performance of the proposed approach in addressing rotor failures, including propeller unloading and motor stoppage. The experimental results demonstrate, for the first time, that our approach enables autonomous quadrotor flight with rotor failures in challenging environments, including cluttered rooms and unknown forests.
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