论文标题
为自动导航进行基准测试视觉定位
Benchmarking Visual Localization for Autonomous Navigation
论文作者
论文摘要
这项工作介绍了基于模拟器的基准测试，用于在自主导航上下文中进行视觉定位。动态基准测试可以调查变量，例如一天中的时间，天气和摄像机视角如何影响使用视觉定位进行闭环控制的自主剂的导航性能。本文的实验部分通过评估最新的视觉定位方法来研究四个此类变量的影响，这是自主导航堆栈运动计划模块的一部分。结果表明，不同方法对基于视力的导航的适用性发生了重大差异。据作者的最佳知识而言，拟议的基准是第一个研究现代视觉定位方法作为完整导航堆栈的一部分的基准。我们在https://github.com/lasuomela/carla_vloc_benchmark上提供基准。
This work introduces a simulator-based benchmark for visual localization in the autonomous navigation context. The dynamic benchmark enables investigation of how variables such as the time of day, weather, and camera perspective affect the navigation performance of autonomous agents that utilize visual localization for closed-loop control. The experimental part of the paper studies the effects of four such variables by evaluating state-of-the-art visual localization methods as part of the motion planning module of an autonomous navigation stack. The results show major variation in the suitability of the different methods for vision-based navigation. To the authors' best knowledge, the proposed benchmark is the first to study modern visual localization methods as part of a complete navigation stack. We make the benchmark available at https://github.com/lasuomela/carla_vloc_benchmark.
