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Sensor Fusion to Detect Scale and Direction of Gravity in Monocular Slam Systems

机译：传感器融合检测单眼血液系统中重力的比例和方向

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摘要

Monocular simultaneous localization and mapping (SLAM) is an important technique that enables very inexpensive environment mapping and pose estimation in small systems such as smart phones and unmanned aerial vehicles. However, the information generated by monocular SLAM is in an arbitrary and unobservable scale, leading to drift and making it difficult to use with other sources of odometry for control or navigation. To correct this, the odometry needs to be aligned with metric scale odometry from another device, or else scale must be recovered from known features in the environment. Typically known environmental features are not available, and for systems such as cellphones or unmanned aerial vehicles (UAV), which may experience sustained, small scale, irregular motion, an IMU is often the only practical option. Because accelerometers measure acceleration and gravity, an inertial measurement unit (IMU) must filter out gravity and track orientation with complex algorithms in order to provide a linear acceleration measurement that can be used to recover SLAM scale. This paper will explore an alternative method, which detects and removes gravity from the accelerometer measurement by using the unscaled direction of acceleration derived from the SLAM odometry.
机译：单眼同时定位和映射（SLAM）是一种重要的技术，使得在诸如智能手机和无人驾驶车辆等小型系统中能够非常便宜的环境映射和姿态估计。然而，单眼血液产生的信息处于任意和不可观察的规模，导致漂移并使其难以与其他内径源进行控制或导航的源。为了纠正此，需要与来自另一个设备的公制刻度测量测量法对齐，或者必须从环境中的已知特征中恢复等距。通常，已知的环境特征不可用，并且对于诸如手机或无人驾驶飞行器（UAV）之类的系统，这可能经历持续，小规模，不规则运动，IMU通常是唯一的实用选项。因为加速度计测量加速度和重力，所以惯性测量单元（IMU）必须用复杂的算法过滤输出重力和轨道方向，以便提供可用于恢复SLAM刻度的线性加速度测量。本文将探讨一种替代方法，其通过使用从船速仪衍生的加速度的未划算方向来检测和消除加速度计测量的重力。

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