# VINS-initialization

**Repository Path**: songziyuan/VINS-initialization

## Basic Information

- **Project Name**: VINS-initialization
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-01-10
- **Last Updated**: 2021-01-10

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# VINS-initialization
In our method, We recover extrinsic rotation, gyroscope bias, metric scale and gravity vector. We do not estimate the velocity but
optimize the extrinsic translation parameter in visual-inertial alignment step. After getting all variables, the velocity can be obtained from the relevant equations. The accelerometer bias is not estimated in this initialization.

**The code frame is based on [**VINS-Mono**](https://github.com/HKUST-Aerial-Robotics/VINS-Mono).**

**The Related Papers**:

**Online Temporal Calibration for Monocular Visual-Inertial Systems**, Tong Qin, Shaojie Shen, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS, 2018). [PDF](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8593603)

**VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator**, Tong Qin, Peiliang Li, Zhenfei Yang, Shaojie Shen, IEEE Transactions on Robotics. [PDF](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8421746)

*We mainly modified the following files: initial_alignment.h, initial_aligment.cpp, visualization.cpp, etc.*