The Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) algorithms which are mostly based on static assumption are widely used in fields such as robotics, UAVs, VR, and autonomous driving. To overcome the localization risks caused by dynamic landmarks in most VI-SLAM systems, a robust visual-inertial motion prior SLAM system, named (IDY-VINS), is proposed in this paper which effectively handles dynamic landmarks using inertial motion prior for dynamic environments to varying degrees. Specifically, potential dynamic landmarks are preprocessed during the feature tracking phase by the probabilistic model of landmarks' minimum projection errors which are obtained from inertial motion prior and epipolar constraint. Subsequently, a bundle adjustment (BA) residual is proposed considering the minimum projection error prior for dynamic candidate landmarks. This residual is integrated into a sliding window based nonlinear optimization process to estimate camera poses, IMU states and landmark positions while minimizing the impact of dynamic candidate landmarks that deviate from the motion prior. Finally, experimental results demonstrate that our proposed system outperforms state-of-the-art methods in terms of localization accuracy and time cost by robustly mitigating the influence of dynamic landmarks.

翻译：基于静态假设的视觉-惯性同步定位与建图（VI-SLAM）算法已广泛应用于机器人、无人机、虚拟现实及自动驾驶等领域。为克服多数VI-SLAM系统中动态路标点引起的定位风险，本文提出一种鲁棒的视觉-惯性运动先验SLAM系统（IDY-VINS），该系统利用惯性运动先验有效处理动态环境中不同程度的动态路标点。具体而言，在特征跟踪阶段，通过惯性运动先验与极线约束获取的路标点最小投影误差概率模型对潜在动态路标点进行预处理。随后，针对动态候选路标点提出一种考虑最小投影误差先验的集束调整（BA）残差项。该残差项被整合至基于滑动窗口的非线性优化过程中，用于估计相机位姿、IMU状态及路标点位置，同时最小化偏离运动先验的动态候选路标点的影响。最终实验结果表明，所提系统通过鲁棒抑制动态路标点的影响，在定位精度与时间成本方面均优于现有先进方法。