# ImuFusion

**Repository Path**: daitole/ImuFusion

## Basic Information

- **Project Name**: ImuFusion
- **Description**: EKF IMU Fusion Algorithms
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-01-07
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ImuFusion
## EKF IMU Fusion Algorithms
1. orien.m uses Kalman filter for fusing the gyroscope's and accelerometer's readings to get the IMU's attitude(quaternion).<br>
2. zupt.m implenments the so called 'zero-velocity-update' algorithm for pedestrian tracking(gait tracking), it's also a ekf filter.<br>
* Video: http://v.youku.com/v_show/id_XMTg2NjI4NTI4NA==.html


## Usage
Example data already included.<br>
Simply run the orien.m or zupt.m. For zupt, set 'CreateVideo' as true if you'd like to save the results as a video.<br>
Note that the datasets and the code for visualizing the results were from:
https://github.com/xioTechnologies/Gait-Tracking-With-x-IMU

## References:
[1] S. Madgwick. An efficient orientation filter for inertial and inertial/magnetic sensor arrays.<br>
[2] Fischer C, et. Implementing a Pedestrian Tracker Using inertial Sensors.<br>
[3] Isaac Skog, et. Zero-Velocity Detection — An Algorithm Evaluation.<br>