Skip to content

About

Implement visual inertial odometry from scratch

Topics

Resources

Stars

4 stars

Watchers

1 watching

Forks

Latest commit

 

History

4 Commits

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 
 
 

Repository files navigation

Stereo MSCKF

See the course website for more details. The code was modified by Dr. Lening Li.

MSCKF (Multi-State Constraint Kalman Filter) is an EKF based tightly-coupled visual-inertial odometry algorithm. S-MSCKF is MSCKF's stereo version. This project is a Python reimplemention of S-MSCKF, the code is directly translated from official C++ implementation KumarRobotics/msckf_vio.

For algorithm details, please refer to:

  • Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight, Ke Sun et al. (2017)
  • A Multi-State Constraint Kalman Filterfor Vision-aided Inertial Navigation, Anastasios I. Mourikis et al. (2006)

Requirements

  • Python 3.6+
  • numpy
  • scipy
  • cv2
  • pangolin (optional, for trajectory/poses visualization)

Dataset

  • EuRoC MAV: visual-inertial datasets collected on-board a MAV. The datasets contain stereo images, synchronized IMU measurements, and ground-truth.
    This project implements data loader and data publisher for EuRoC MAV dataset.

Run

python vio.py --view --path path/to/your/EuRoC_MAV_dataset/MH_01_easy
or
python vio.py --path path/to/your/EuRoC_MAV_dataset/MH_01_easy (no visualization)

Results

MH_01_easy

License and References

Follow license of msckf_vio. Code is adapted from this implementation.

About

Implement visual inertial odometry from scratch

Topics

Resources

Stars

4 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages