CVIDS: A Collaborative Localization and Dense Mapping Framework for Multi-agent Based Visual-inertial SLAM

1. Prerequisites

We have tested the library in Ubuntu 16, but it should be easy to compile in other platforms.

C++11 or C++0x Compiler

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

ROS-Kinetic

CVIDS is implemented based on ROS-Kinetic. More details can be found in http://wiki.ros.org/kinetic/Installation.

Sophus

This is an Lie algebra library. More details can be found in https://github.com/strasdat/Sophus.

OpenCV

We use OpenCV to manipulate images and features. Dowload and install instructions can be found at: http://opencv.org. We use 3.4.1, but it should also work for other version at least 3.0.

Eigen3

Download and install instructions can be found at: http://eigen.tuxfamily.org.

ceres-solver

We use ceres library to perform non-linear optimizations.

2. Tested data

Tested data can be found in https://pan.baidu.com/s/1L0krS1lXO4hmUnO8MXqFwQ, Extraction code: ear2

3. Building the project

Just prepare the ros workspace and clone CVIDS to the src directory of the workspace. Then use "catkin_make" to build the project. After the compilation， use roslaunch server_pose_graph collaborative.launch to activate the pipeline.