基于单目视觉方向约束的惯性碰撞无缝辅助

U. Qayyum, Jonghyuk Kim
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引用次数: 6

摘要

惯性slam可以为自主机器人提供全六自由度信息的全地形导航能力,因此受到了人们的积极研究。随着最近低成本惯性和视觉传感器的可用性,轻量级和精确的测绘系统可以实现许多机器人任务,如陆地/空中勘探。实现这一目标的关键挑战是如何获得可靠和持续的辅助信息来纠正固有不稳定的惯性系统。现有的方法一直依赖于基于特征的地图,这需要精确的深度分辨率过程来正确地校正惯性单元,其中辅助速率高度依赖于地图密度。在这项工作中,我们提出通过融合尺度模糊平移向量作为车辆运动的视觉方向约束(VDC),以高更新率将视觉里程计直接集成到惯性系统中,而3D地图仍然用于约束纵向漂移,但以一种宽松的方式。通过解决惯性相机与单目相机之间的尺度模糊问题,将视觉里程计信息无缝融合到惯性系统中,从而实现可靠、持续的辅助。在SLAM基准数据集和仿真环境上对该方法进行了评估,结果表明该方法具有更加稳定和一致的单目惯性SLAM性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seamless aiding of inertial-slam using Visual Directional Constraints from a monocular vision
Inertial-SLAM has been actively studied as it can provide all-terrain navigational capability with full six degrees-of-freedom information to autonomous robots. With the recent availability of low-cost inertial and vision sensors, a light-weight and accurate mapping system could be achieved for many robotic tasks such as land/aerial explorations. The key challenge toward this is in the availability of reliable and constant aiding information to correct the inertial system which is intrinsically unstable. The existing approaches have been relying on feature-based maps, which require accurate depth-resolution process to correct the inertial units properly where the aiding rate is highly dependent on the map density. In this work we propose to directly integrate the visual odometry to the inertial system by fusing the scale ambiguous translation vectors as Visual Directional Constraints (VDC) on vehicle motion at high update rates, while the 3D map being still used to constrain the longitudinal drifts but in a relaxed way. In this way, the visual odometry information can be seamlessly fused to inertial system by resolving the scale ambiguity problem between inertial and monocular camera thus achieving a reliable and constant aiding. The proposed approach is evaluated on SLAM benchmark dataset and simulated environment, showing a more stable and consistent performance of monocular inertial-SLAM.
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