**Chunlin Song, Xiaogang Wang \* and Naigang Cui**

School of Astronautics, Harbin Institute of Technology, Harbin 150001, China; 14b918036@hit.edu.cn (C.S.); cui\_naigang@163.com (N.C.)

**\*** Correspondence: wangxiaogang@hit.edu.cn; Tel.: +86-0451-8641-3459

Received: 3 December 2018; Accepted: 17 December 2018; Published: 24 December 2018

**Abstract:** Visual–inertial odometry is an effective system for mobile robot navigation. This article presents an egomotion estimation method for a dual-sensor system consisting of a camera and an inertial measurement unit (IMU) based on the cubature information filter and *H*∞ filter. The intensity of the image was used as the measurement directly. The measurements from the two sensors were fused with a hybrid information filter in a tightly coupled way. The hybrid filter used the third-degree spherical-radial cubature rule in the time-update phase and the fifth-degree spherical simplex-radial cubature rule in the measurement-update phase for numerical stability. The robust *H*∞ filter was combined into the measurement-update phase of the cubature information filter framework for robustness toward non-Gaussian noises in the intensity measurements. The algorithm was evaluated on a common public dataset and compared to other visual navigation systems in terms of absolute and relative accuracy.

**Keywords:** visual-inertial odometry; cubature information filter; navigation; IMU; RGBD camera
