Bidirectional Trajectory Computation for Odometer-Aided Visual-Inertial SLAM

Abstract

Odometer-aided visual-inertial SLAM systems typically have a good performance for navigation of wheeled platforms, while they usually suffer from degenerate cases before the first turning. In this paper, firstly we perform an observability analysis w.r.t. the extrinsic parameters before the first turning, which is a complement of the existing results of observability analyses. Secondly, inspired by the above observability analyses, we propose a bidirectional trajectory computation method, by which the poses before the first turning are refined in the backward computation thread, and the real-time trajectory is adjusted accordingly. Experimental results prove that our proposed method not only solves the problem of the unobservability of accelerometer bias and extrinsic parameters before the first turning, but also results in more accurate trajectories in comparison with the state-of-the-art approaches.

arXiv commentAccepted by IEEE Robotics and Automation Letters

References in corpus (4)

• VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator
• Tightly-coupled Monocular Visual-odometric SLAM using Wheels and a MEMS Gyroscope
• Observability-aware Self-Calibration of Visual and Inertial Sensors for Ego-Motion Estimation
• Fast and Robust Initialization for Visual-Inertial SLAM

Cited by in corpus (1)

• Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models