评测无人机在无GPS环境下的自主导航能力，验证算法与感知系统有效性。
Threading the Needle: Test and Evaluation of Early Stage UAS Capabilities to Autonomously Navigate GPS-Denied Environments in the DARPA Fast Lightweight Autonomy (FLA) Program
- 基于统一硬件平台，对比三支团队的自主导航算法与感知方案。
- 在室内外复杂环境中完成多阶段实验，验证无人机在无定位信号下的飞行性能。
- 适合研究自主导航、无人机集群和机器人感知的科研人员参考。
DARPA快速轻量自主（FLA）计划（2015–2018年）是无人航空系统（UAS）自主导航发展的重要里程碑，尤其聚焦于未知环境下无全球导航卫星系统（GPS）支持的自主飞行。三个表现优异的团队采用同一硬件平台，重点研发自主算法与感知技术。实验覆盖室内外环境，难度逐步递增。本文回顾了用于评估各团队表现的测试方法，详述了FLA第一阶段的所有实验设计，并总结了该阶段的核心成果。
原文摘要 · Abstract (English)
The DARPA Fast Lightweight Autonomy (FLA) program (2015 - 2018) served as a significant milestone in the development of UAS, particularly for autonomous navigation through unknown GPS-denied environments. Three performing teams developed UAS using a common hardware platform, focusing their contributions on autonomy algorithms and sensing. Several experiments were conducted that spanned indoor and outdoor environments, increasing in complexity over time. This paper reviews the testing methodology developed in order to benchmark and compare the performance of each team, each of the FLA Phase 1 experiments that were conducted, and a summary of the Phase 1 results.
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。