Aligning a robot's trajectory or map to the inertial frame is a critical capability that is often difficult to do accurately even though inertial measurement units (IMUs) can observe absolute roll and pitch with respect to gravity. Accelerometer biases and scale factor errors from the IMU's initial calibration are often the major source of inaccuracies when aligning the robot's odometry frame with the inertial frame, especially for low-grade IMUs. Practically, one would simultaneously estimate the true gravity vector, accelerometer biases, and scale factor to improve measurement quality but these quantities are not observable unless the IMU is sufficiently excited. While several methods estimate accelerometer bias and gravity, they do not explicitly address the observability issue nor do they estimate scale factor. We present a fixed-lag factor-graph-based estimator to address both of these issues. In addition to estimating accelerometer scale factor, our method mitigates limited observability by optimizing over a time window an order of magnitude larger than existing methods with significantly lower computational burden. The proposed method, which estimates accelerometer intrinsics and gravity separately from the other states, is enabled by a novel, velocity-agnostic measurement model for intrinsics and gravity, as well as a new method for gravity vector optimization on S2. Accurate IMU state prediction, gravity-alignment, and roll/pitch drift correction are experimentally demonstrated on public and self-collected datasets in diverse environments.

翻译：将机器人轨迹或地图与惯性坐标系对齐是一项关键能力，即使惯性测量单元（IMU）能够观测到相对于重力的绝对横滚角和俯仰角，这一对齐过程仍常难以精确实现。在将机器人里程计坐标系与惯性坐标系对齐时，IMU初始校准产生的加速度计偏置和比例因子误差通常是精度不足的主要来源，尤其对于低精度IMU而言。实践中，人们会同时估计真实重力向量、加速度计偏置和比例因子以提升测量质量，但这些量在IMU未充分激励时并不可观测。尽管已有多种方法估计加速度计偏置和重力，但它们既未明确解决可观测性问题，也未估计比例因子。我们提出一种基于固定滞后因子图的估计器来应对这两个问题。除了估计加速度计比例因子外，我们的方法通过将优化时间窗口扩大至现有方法一个数量级以上，并显著降低计算负担，从而缓解了有限可观测性问题。所提出的方法将加速度计内参和重力与其他状态分开估计，这得益于我们提出的用于内参和重力的新型速度无关测量模型，以及一种S2流形上的重力向量优化新方法。通过在多样化环境中的公开数据集和自采集数据集上的实验，我们验证了该方法在精确IMU状态预测、重力对齐以及横滚/俯仰漂移校正方面的有效性。