Global Navigation Satellite System/Inertial Navigation System (GNSS/INS)/Vision integration based on factor graph optimization (FGO) has recently attracted extensive attention in navigation and robotics community. Integrity monitoring (IM) capability is required when FGO-based integrated navigation system is used for safety-critical applications. However, traditional researches on IM of integrated navigation system are mostly based on Kalman filter. It is urgent to develop effective IM scheme for FGO-based GNSS/INS/Vision integration. In this contribution, the position error bounding formula to ensure the integrity of the GNSS/INS/Vision integration based on FGO is designed and validated for the first time. It can be calculated by the linearized equations from the residuals of GNSS pseudo-range, IMU pre-integration and visual measurements. The specific position error bounding is given in the case of GNSS, INS and visual measurement faults. Field experiments were conducted to evaluate and validate the performance of the proposed position error bounding. Experimental results demonstrate that the proposed position error bounding for the GNSS/INS/Vision integration based on FGO can correctly fit the position error against different fault modes, and the availability of integrity in six fault modes is 100% after correct and timely fault exclusion.

翻译：基于因子图优化（FGO）的全球导航卫星系统/惯性导航系统（GNSS/INS）/视觉融合技术近年来在导航与机器人领域受到广泛关注。当基于FGO的融合导航系统用于安全关键型应用时，必须具备完整性监测（IM）能力。然而，传统关于融合导航系统完整性监测的研究大多基于卡尔曼滤波器。因此，迫切需要为基于FGO的GNSS/INS/视觉融合开发有效的完整性监测方案。本文首次设计并验证了用于确保基于FGO的GNSS/INS/视觉融合完整性的定位误差限界公式。该公式可通过GNSS伪距、IMU预积分及视觉测量残差的线性化方程进行计算。文中具体给出了在GNSS、INS及视觉测量发生故障情况下的定位误差限界。通过现场实验对所提定位误差限界方法的性能进行了评估与验证。实验结果表明，所提出的基于FGO的GNSS/INS/视觉融合定位误差限界能够正确拟合不同故障模式下的定位误差，并且在正确及时地排除故障后，六种故障模式下的完整性可用性均达到100%。