Yet another Visual Odometer (YaVO)

A SLAM algorithm written in C++ for ego-motion estimation and environment reconstruction with a RGB-D camera.

Video demonstration:

Installation

First, make sure you have the following packages installed:

• OpenCV 3
• PCL >= 1.8
• G2O
• Eigen 3
• SuiteSparse
• Spdlog

Then clone this repo into a local folder. Then run the good 'ol stuff:

mkdir build
cd build
cmake ..
make

Now you can find the executable in bin/ folder of our project root.

Usage

We recommend evaluating our algorithm with TUM dataset. Our program reads the associated image sequence generated by associate.py.

To use our algorithm, simply do:

RGBDSlamApp path_to_associate_txt start_seq end_seq parameters.txt

Explanation:

path_to_associate_txt: associated image sequence file generated by associate.py

start_seq/end_seq: Image sequence range used for reconstruction

parameters.txt: program configurations(see below)

Parameter File Format

We have provided you a template parameter file located in misc/parameters.txt. The content of this file is very straight-forward. However, there might be a few more things you need to notice before beginning.

• If you are using the images extracted from your own Kinect / Xtion / etc, you have to fill in the calibrated intrinsics beforehand.
• Standard feature extractors (SIFT SURF ORB FAST) and descriptors (SIFT SURF ORB BRISK) etc are supported

Note

Currently I have not implemented the interface with ROS, therefore online SLAM is not supported yet.