Authors: ORB SLAM 2 Raul Mur-Artal, Juan D. Tardos, J. M. M. Montiel and Dorian Galvez-Lopez (DBoW2)
Authors: Active ORB SLAM 2 Xinke Deng, Zixu Zhang, Avishai Sintov, Jing Huang, and Timothy Bretl
#1. Prerequisites We have tested the library in 14.04 with ROS indigo. A powerful computer (e.g. i7) will ensure real-time performance and provide more stable and accurate results.
We use the new thread and chrono functionalities of C++11.
We use Pangolin for visualization and user interface. Dowload and install instructions can be found at: https://github.com/stevenlovegrove/Pangolin.
We use OpenCV to manipulate images and features. Dowload and install instructions can be found at: http://opencv.org. Required at leat 2.4.3. Tested with OpenCV 2.4.11 and OpenCV 3.2.
Required by g2o (see below). Download and install instructions can be found at: http://eigen.tuxfamily.org. Required at least 3.1.0.
We use modified versions of the DBoW2 library to perform place recognition and g2o library to perform non-linear optimizations. Both modified libraries (which are BSD) are included in the Thirdparty folder.
ROS indigo is required ros.
OctoMap is required octomap
OMPL is required OMPL
#2. Building Active-ORB-SLAM2 library
Clone the repository:
git clone https://github.com/XinkeAE/Actuve-ORB-SLAM2.git
cd Active-ORB-SLAM2
chmod +x build.sh
./build.sh
This will create libORB_SLAM2.so at lib folder and the executables mono_tum, mono_kitti, rgbd_tum, stereo_kitti, mono_euroc and stereo_euroc in Examples folder.
#3. Building ROS
chmod +x build_ros.sh
./build_ros.sh
#4. Specify the goal pose in planning.cc and system.cc changing line 265 - 268 in system.cc
#5. Run ros driver by running the script
./kinect.sh