slambook-en VS ORB_SLAM2

Looking at code repos is not an effective way to learn in my opinion. I highly recommend this open text book that has practical explained and many code examples https://github.com/gaoxiang12/slambook-en

According to a popular slam book(https://github.com/gaoxiang12/slambook-en/blob/master/slambook-en.pdf) this has to do with solving the Hx=g with schur trick and how row operations induce some implicit constraints during the marginalization step ( pg 211~213). However, I don't think I am getting the full picture here.

Hi, I work on a tangentially related topic and the best resource I've found so far is this book: https://github.com/gaoxiang12/slambook-en/blob/master/slambook-en.pdf. I went through some chapters only, but everything seems to be explained clearly and with code examples. Hope this helps!

I am trying to understand the Lie algebra for robotics and reading up this: https://github.com/gaoxiang12/slambook-en/blob/master/slambook-en.pdf

If you're wanting to learn how all this stuff works I highly recommend this open source book: https://github.com/gaoxiang12/slambook-en

Hey! I was in your shoes a couple months ago! The YouTube video that the_remainder posted is how I wrapped my mind around lie algebra, but in order for me to be able to use it effectively took going through the relevant chapter in the slambook (https://github.com/gaoxiang12/slambook-en)

Great book to learn slam https://github.com/gaoxiang12/slambook-en

https://github.com/gaoxiang12/slambook-en I would recommend this.

ORB_SLAM2 on GitHub: https://github.com/raulmur/ORB_SLAM2

Hi everyone, I am trying to implement a VSLAM with DNN specifically the Feature Extraction module in the SLAM pipeline. Something on the lines of this repo Superpoint_SLAM , which integrates SuperPoint Feature extraction into ORB_SLAM2

Maybe you could give Orb-SLAM2 a try with a Pi cam. The package says it works with a monocular camera. https://github.com/raulmur/ORB_SLAM2

I am thinking about migrating ORBSLAM2(written in cpp) to python3. Currently there are only python3 wrappers for ORBSLAM2, like ORB_SLAM2-PythonBindings and pyORBSLAM2. The biggest problem is that I can't easily and quickly improve, change all the stuff in cpp, as it would be in python. I am aware that the cpp code is much faster the python equivalent, but implementing and improving additional features is much easier in python, at least for me. For converting the code, I'll keep the optimization stuff like g2o(g2opy), pangolin(pypangolin) and DBoW2(pyDBoW) in cpp, but the rest should be in pure python code.

This repo has an advanced SLAM implementation. They also link to a few research papers about how this group made this SLAM algorithm. The ORB SLAM 2 paper has all of the parts of modern SLAM systems, so I'd read that, and the other papers if you have time at the end.

Example: https://github.com/raulmur/ORB_SLAM2/blob/f2e6f51cdc8d067655d90a78c06261378e07e8f3/Examples/ROS/ORB_SLAM2/src/ros_stereo.cc#L71

I'm not sure what your final application is, but you can use a SLAM algorithm to recover your camera trajectory. I've used ORB SLAM 2, and it's pretty nice.