justagist / monocular_visual_graph_slam

An implementation of Graph-based SLAM using only an onboard monocular camera. Developed as part of MSc Robotics Masters Thesis (2017) at University of Birmingham.

Visual Graph-Based SLAM (ROS Package)

An implementation of Graph-based SLAM using just a sequence of image from a monocular camera. It performs feature-based visual odometry (requires STAM library) and graph optimisation using g2o library.

Video

Watch implementation of the algorithm on an aerial robot (Parrot AR.Drone) here

Dependencies

• OpenCV 2.4.x (non-free version)
• LAPACK
• g2o (included. Follow installation instructions)
• Suite-Sparse

TODO

• Remove dependency on PCL (not presently using the library any more)

Installation (Tested on ROS indigo + Ubuntu 14.04)

cd <catkin_workspace>/src/
git clone https://[email protected]/justagist/graph_slam.git

## build g2o library ##
cd graph_slam/EXTERNAL/g2o/ 
cmake . && make 

## clone STAM library (branch - graphslam_mod) for visual odometry ##
cd ..
git clone -b graphslam_mod https://github.com/eaa3/STAM.git
cd STAM/
mkdir build && cd build
cmake ..
make -j

## build package ##
cd <catkin_workspace>/
catkin_make
source devel/setup.bash

Usage

Before running the graph-slam node, the location of the 'fabmap_training_data' folder has to be entered by editing the value of 'fabmap_training_data_destination_' parameter in graph_slam/src/main.cpp file. The path to the image dataset on which the algorithm is to be run can also be set in the main.cpp file.

Running graph-slam node:

rosrun graph_slam main_slam_node <scene_number> [visualize?] [publish rostopics?] [save trajectory to txt file?] [run graph optimisation thread?] [baseline for visual odometry] [trajectory file name] 

Run rosrun graph_slam main_slam_node for detailed usage instructions

Other nodes

• Plot trajectory output from graph_slam: rosrun graph_slam trajectory_plotter.py <trajectory_file.txt>
• Plot and compare 2 trajectories: rosrun graph_slam compare_trajectories.py <trajectory_file_1.txt> <trajectory_file_2.txt>
• Compare trajectory with ground_truth (if available): rosrun graph_slam groundtruth_compare.py <trajectory_file.txt> <groundtruth.txt>

Function and usage of all nodes are described in the respective source files, along with the format of the input files (where required).