https://github.com/kemfic/simple-slam

wip - a simple slam implementation so i can learn stuff
https://github.com/kemfic/simple-slam

computer-vision multiple-view-geometry opencv opencv3 python3 robotics slam visual-odometry

Last synced: 3 months ago
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wip - a simple slam implementation so i can learn stuff

• Host: GitHub
• URL: https://github.com/kemfic/simple-slam
• Owner: kemfic
• License: mit
• Created: 2018-10-07T17:58:32.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-04-23T19:01:58.000Z (almost 5 years ago)
• Last Synced: 2023-10-20T02:09:52.520Z (over 1 year ago)
• Topics: computer-vision, multiple-view-geometry, opencv, opencv3, python3, robotics, slam, visual-odometry
• Language: Python
• Homepage:
• Size: 79.2 MB
• Stars: 17
• Watchers: 2
• Forks: 4
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# simple-SLAM

A crappy visual SLAM implementation I'm working on to learn stuff. Still a work in progress.

refactor coming at some point

[video playlist](https://www.youtube.com/playlist?list=PLz9N52s5FSIUFNoLjyNy_9EW42Ngy6ipn)

![pointcloud](resources/pointcloud.png)

## todo

   - add keyframes

   - refactor everything

   - figure out what bundle adjustment is

## how to use

   - not sure if I can share the datasets i'm using, so just put any video file in the `vids/` folder

   - currently only have visual odometry barely working, so just run `python stream.py` to see it working

want to learn more about slam/visual odometry?

---

   - check out Multiple View Geometry by Hartley & Zissermann

   - [Avi Singh's visual odometry projects](https://github.com/avisingh599/mono-vo)

   - [twitchslam by geohot](https://github.com/geohot/twitchslam)

   - [UZH and ETH Zurich's course (Vision Algorithms for Mobile Robotics)](https://web.archive.org/web/20171231011504/http://rpg.ifi.uzh.ch/teaching.html)

   - S-PTAM, PTAM, ORB-SLAM, LSD-SLAM

     - papers and code are super useful

   - OpenCV references in API documentation

     - look in the SFM modules

## dependencies

   - OpenCV

   - Numpy

   - Scikit-image

   - pangolin (we use uoip's fork for its bindings, since its a bit more python-friendly and intuitive)

      - https://github.com/uoip/pangolin

## LOICENSE

MIT license. Do what you want with it, but please attribute my work if you do. Also don't sue me.