Formula Derivation and Analysis of the VINS-Mono
This work provides a detailed derivation for an existing method, which is incremental for researchers and practitioners in robotics and computer vision.
The authors derived and analyzed the main equations of the VINS-Mono, a monocular visual-inertial state estimator, focusing on IMU pre-integration, visual-inertial co-initialization, and tightly-coupled nonlinear optimization.
The VINS-Mono is a monocular visual-inertial 6 DOF state estimator proposed by Aerial Robotics Group of HKUST in 2017. It can be performed on MAVs, smartphones and many other intelligent platforms. Because of the excellent robustness, accuracy and scalability, it has gained extensive attention worldwide. In this manuscript, the main equations including IMU pre-integration, visual-inertial co-initialization and tightly-coupled nonlinear optimization are derived and analyzed.