在嵌入式设备上实现高速无GPS飞行的实时热惯性里程计。
Real-Time Thermal-Inertial Odometry on Embedded Hardware for High-Speed GPS-Denied Flight

- 融合热成像、惯性、激光测距等多源数据,构建固定滞后因子图。
- 30米/秒下飞行时,千米级轨迹漂移低于2%,抗振动能力强。
- 适合高动态、低光照或无信号环境下的无人机自主导航。
我们提出一种面向高速、无GPS飞行的实时单目热惯性里程计系统,运行于嵌入式硬件平台。系统融合FLIR Boson+ 640长波红外相机、高频率IMU、激光测距仪、气压计和磁力计,在固定滞后因子图中进行数据融合。为应对运动模糊、对比度低和视角快速变化带来的挑战,采用轻量化热优化前端,结合多阶段特征过滤。激光测距提供每特征点深度先验,稳定弱可观测运动下的尺度。高频率惯性数据先经切比雪夫II型无限冲激响应(IIR)滤波预处理,再进行预积分,有效提升剧烈机动时对机体振动的鲁棒性。针对高速飞行引发的气压高度误差,训练了一种考虑不确定性的门控循环单元(GRU)网络,建模静压畸变的时间动态,性能优于多项式与多层感知机(MLP)基线。系统集成于NVIDIA Jetson Xavier NX,支持闭环四旋翼飞行,速度达30米/秒,千米级轨迹漂移低于2%。本工作拓展了热惯性导航的应用边界,可在视觉退化且无GPS环境下实现可靠高速飞行。
原文摘要 · Abstract (English)
We present a real-time monocular thermal-inertial odometry system designed for high-velocity, GPS-denied flight on embedded hardware. The system fuses measurements from a FLIR Boson+ 640 longwave infrared camera, a high-rate IMU, a laser range finder, a barometer, and a magnetometer within a fixed-lag factor graph. To sustain reliable feature tracks under motion blur, low contrast, and rapid viewpoint changes, we employ a lightweight thermal-optimized front-end with multi-stage feature filtering. Laser range finder measurements provide per-feature depth priors that stabilize scale during weakly observable motion. High-rate inertial data is first pre-filtered using a Chebyshev Type II infinite impulse response (IIR) filter and then preintegrated, improving robustness to airframe vibrations during aggressive maneuvers. To address barometric altitude errors induced at high airspeeds, we train an uncertainty-aware gated recurrent unit (GRU) network that models the temporal dynamics of static pressure distortion, outperforming polynomial and multi-layer perceptron (MLP) baselines. Integrated on an NVIDIA Jetson Xavier NX, the complete system supports closed-loop quadrotor flight at 30 m/s with drift under 2% over kilometer-scale trajectories. These contributions expand the operational envelope of thermal-inertial navigation, enabling reliable high-speed flight in visually degraded and GPS-denied environments.
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