用蓝牙阵列和因子图优化，实现无人机在无卫星信号时的高精度定位。
Bluetooth Phased-array Aided Inertial Navigation Using Factor Graphs: Experimental Verification
- 基于因子图优化，融合蓝牙角度与距离信息提升导航精度。
- 实验显示在失锁卫星信号下定位误差小于1.5米，性能优于传统方法。
- 适合做低成本无人机、仓储机器人等室内外切换场景的导航系统研究者。
相控阵蓝牙系统已成为一类低成本方案，用于在无全球导航卫星系统（GNSS）环境下开展辅助惯性导航，例如仓库物流、无人机着陆和自主对接等场景。采用商用现成组件可降低相控阵无线电导航系统的进入门槛，但会带来显著更嘈杂的测量数据和相对较短的有效作用范围。本文利用多旋翼无人机飞行采集的实验数据，对比了基于因子图优化的估计器所采用的多种鲁棒估计策略。评估了在失去GNSS信号的情况下，利用蓝牙角度测量以及距离或气压计信息进行辅助时的性能表现。
原文摘要 · Abstract (English)
Phased-array Bluetooth systems have emerged as a low-cost alternative for performing aided inertial navigation in GNSS-denied use cases such as warehouse logistics, drone landings, and autonomous docking. Basing a navigation system off of commercial-off-the-shelf components may reduce the barrier of entry for phased-array radio navigation systems, albeit at the cost of significantly noisier measurements and relatively short feasible range. In this paper, we compare robust estimation strategies for a factor graph optimisation-based estimator using experimental data collected from multirotor drone flight. We evaluate performance in loss-of-GNSS scenarios when aided by Bluetooth angular measurements, as well as range or barometric pressure.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。