外观
论文arXiv 2610.0727823 天前
嵌入式裸机雷达-惯性里程计
原文链接：Embedded Bare-Metal Radar-Inertial Odometry（arXiv 2610.07278 · 发布日期：2026-10-05）
Embedded Bare-Metal Radar-Inertial Odometry
面向低算力平台的鲁棒状态估计，提出单核微控制器上的雷达-惯性估计器，并在飞行实验中验证。
核心要点
- 视觉或LiDAR方案计算开销高，且易受感知退化环境影响。
- 利用FMCW雷达直接速度测量与抗感知退化能力，融合惯性导航。
- 飞行实验对比动捕APE为0.51-0.82 m，RPE小于3%。
- 通过未修改PX4闭环飞行，固件和PCB设计已在GitHub开源。
验证范围与局限：验证范围为飞行实验：对比运动捕捉并通过未修改PX4进行闭环飞行。
英文摘要 (Abstract)
Compact extraplanetary rovers and micro aerial vehicles require robust state estimation frameworks designed to operate under strict computational constraints in unforgiving environments. Typical solutions involving vision- or LiDAR-based sensing are computationally expensive and vulnerable to environments with perceptual degradation, making them poorly suited for resource-constrained platforms and austere conditions. Alternatively, Frequency Modulated Continuous Wave (FMCW) radar offers both robustness and computational efficiency by directly providing velocity measurements coupled with inherent resilience to perceptual degradation. These factors enable robust estimation, thereby reducing reliance on human operators for supervision to ensure platform safety in challenging environments. In this manuscript, we propose an embedded radar-inertial estimator tailored for low-compute platforms. All sensor drivers, data processing, and aided inertial navigation are performed on a single-core microcontroller, demonstrating its computational efficiency. Flight experiments show translational APE of $0.51-0.82,\mathrm{m}$ and RPE of $<$3,% against motion capture, alongside closed-loop flight through an unmodified PX4 stack. The firmware and printed circuit board design are openly available on GitHub at https://github.com/ntnu-arl/embedded_rio and https://github.com/ntnu-arl/embedded_rio-pcb respectively.
作者：Nicolai Adil Øyen Aatif, Morten Nissov, Kostas Alexis
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