论文标题
立体视觉惯性大满贯系统的闭环基准测试：了解漂移和潜伏期对跟踪准确性的影响
Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy
论文作者
论文摘要
视觉惯性大满贯对于在受GPS有限的环境中的机器人导航至关重要，例如室内，地下。通常，通过开环分析评估视觉惯性大满贯的性能，重点是SLAM系统的漂移水平。在本文中，我们提出了有关闭环导航任务中视觉估计延迟的重要性的问题，例如准确的轨迹跟踪。为了了解漂移和潜伏期对视觉惯性大满贯系统的影响，进行了闭环基准测试模拟，在该模拟中，命令机器人使用Visual持久估计的反馈遵循所需的轨迹。通过广泛评估代表性最先进的视觉惯性大满贯系统的轨迹跟踪性能，我们揭示了这些系统视觉估计模块中延迟降低的重要性。这些发现暗示了视觉惯性大满贯未来改进的方向。
Visual-inertial SLAM is essential for robot navigation in GPS-denied environments, e.g. indoor, underground. Conventionally, the performance of visual-inertial SLAM is evaluated with open-loop analysis, with a focus on the drift level of SLAM systems. In this paper, we raise the question on the importance of visual estimation latency in closed-loop navigation tasks, such as accurate trajectory tracking. To understand the impact of both drift and latency on visual-inertial SLAM systems, a closed-loop benchmarking simulation is conducted, where a robot is commanded to follow a desired trajectory using the feedback from visual-inertial estimation. By extensively evaluating the trajectory tracking performance of representative state-of-the-art visual-inertial SLAM systems, we reveal the importance of latency reduction in visual estimation module of these systems. The findings suggest directions of future improvements for visual-inertial SLAM.
