CERES-MONO-ORB-SLAM2-ROS

1. Prerequisites

C++11 Compiler

We use the new thread and chrono functionalities of C++11.

OpenCV

We use OpenCV to manipulate images and features. Dowload and install instructions can be found at: http://opencv.org. Tested with OpenCV 3.4.3.

Eigen3

Required by g2o (see below). Download and install instructions can be found at: http://eigen.tuxfamily.org. Tested with Eigen3 3.3.4.

Ceres-Solver

We use Ceres-Solver to perform optimization. Dowload and install instructions can be found at: http://www.ceres-solver.org/index.html.

DBoW2 (Included in Thirdparty folder)

We use modified versions of the DBoW2 library to perform place recognition. The modified library is included in the Thirdparty folder.

ROS

You need to install ROS first. Install instruction can be found at: http://wiki.ros.org/ROS/Installation. We just tested ROS melodic version.

2. Building ORB-SLAM2 library and examples

create workspace:

mkdir -p catkin_ws/src
cd catkin_ws/src
catkin_init_workspace
cd ..
catkin_make
source devel/setup.bash

Clone the repository:

cd src
git clone -b g2o-ros https://github.com/lh9171338/MONO-ORB-SLAM2.git

We provide a script build.sh to build the Thirdparty libraries. Please make sure you have installed all required dependencies (see section 1). Execute:

cd MONO-ORB-SLAM2
chmod +x build.sh
./build.sh

Build the package:

cd ../..
catkin_make

3. Examples

TUM Dataset

1. Download a bag file from http://vision.in.tum.de/data/datasets/rgbd-dataset/download.

2. Edit the script scripts/mono_tum.sh and the launch filelaunch/mono_tum.launch according to the dataset, then execute the following command.

./scripts/mono_tum.sh 

EuRoC Dataset

1. Download a bag file from http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets.

2. Edit the script scripts/mono_euroc.sh and the launch file launch/mono_euroc.launch according to the dataset, then execute the following command.

./scripts/mono_euroc.sh