What is ORB-SLAM3?

ORB-SLAM3 (Oriented FAST and Rotated BRIEF Simultaneous Localization and Mapping) is a state-of-the-art SLAM system designed for robust and accurate real-time 3D mapping and localization. It supports monocular, stereo, and RGB-D cameras and integrates visual-inertial sensor fusion for increased robustness in challenging environments.

Key Features:

• Multi-Sensor Support: Works with monocular, stereo, RGB-D, and visual-inertial sensors.
• Versatility: Can operate in static and dynamic environments, making it suitable for a wide range of applications.
• Real-Time Performance: Optimized for high-speed processing and efficient mapping.
• Loop Closing and Relocalization: Ensures accurate and drift-free localization over long distances.

Applications:

1. Robotics: Autonomous navigation, obstacle avoidance, and robotic arm manipulation.
2. Augmented Reality (AR): Seamless integration of virtual objects into real-world environments.
3. Autonomous Vehicles: Localization and mapping for self-driving cars and drones.
4. 3D Reconstruction: Creating detailed 3D models of environments for analysis and simulation.

General Info:

• Developers: Created by the UZ-SLAMLab team.
• Platform: Designed for Linux-based systems and requires dependencies like OpenCV, Pangolin, and Eigen.
• Open Source: Available under the GPLv3 license, allowing for free use and modification.
• Documentation: The official GitHub repository provides detailed instructions and examples.

For more information, visit the ORB-SLAM3 GitHub Repository.

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ORB-SLAM3 Installation Guide for Beginners

Introduction

ORB-SLAM3 is a state-of-the-art system for Simultaneous Localization and Mapping (SLAM). This guide is tailored for beginners and includes detailed steps for installing ORB-SLAM3 on Ubuntu.

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Step 1: Update Your System

Before starting, ensure your system is up-to-date.

sudo apt update
sudo apt upgrade

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Step 2: Install Essential Tools and Libraries

ORB-SLAM3 requires several dependencies. Install them using the following commands:

sudo apt install build-essential cmake git libgtk2.0-dev pkg-config \
libavcodec-dev libavformat-dev libswscale-dev python3 python3-numpy \
libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libdc1394-22-dev \
libjasper-dev libglew-dev libboost-all-dev libssl-dev libeigen3-dev unzip wget

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Step 3: Install OpenCV (Version 4.6.0)

OpenCV is a computer vision library required for ORB-SLAM3.

1. Download OpenCV:

cd ~
mkdir Dev && cd Dev
git clone https://github.com/opencv/opencv.git
cd opencv
git checkout 4.6.0

2. Build OpenCV:

mkdir build && cd build
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local ..
make -j$(nproc)  # Use all CPU cores for faster compilation
sudo make install

3. Verify Installation:

pkg-config --modversion opencv4

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Step 4: Install Pangolin

Pangolin is required for visualizing SLAM results.

1. Download Pangolin:

cd ~/Dev
git clone https://github.com/stevenlovegrove/Pangolin.git
cd Pangolin

2. Build Pangolin:

mkdir build && cd build
cmake .. -D CMAKE_BUILD_TYPE=Release
make -j$(nproc)
sudo make install

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Step 5: Clone and Build ORB-SLAM3

1. Clone the Repository:

cd ~/Dev
git clone https://github.com/UZ-SLAMLab/ORB_SLAM3.git
cd ORB_SLAM3

2. Update Compiler Flags:

ORB-SLAM3 requires C++14. Modify the CMakeLists.txt file:

sed -i 's/++11/++14/g' CMakeLists.txt

3. Build ORB-SLAM3:

./build.sh

If you encounter errors, try running the build script again.

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Step 6: Download Vocabulary File

ORB-SLAM3 requires a vocabulary file for its operation.

1. Download Vocabulary:

cd ~/Dev/ORB_SLAM3/Vocabulary
wget https://github.com/raulmur/ORB_SLAM2/raw/master/Vocabulary/ORBvoc.txt.tar.gz
tar -xvzf ORBvoc.txt.tar.gz
rm ORBvoc.txt.tar.gz

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Step 7: Download a Dataset for Testing

You can test ORB-SLAM3 using the EuRoC MAV dataset.

1. Create a Directory for Datasets:

cd ~
mkdir -p Datasets/EuRoc && cd Datasets/EuRoc

2. Download a Sample Dataset:

wget -c http://robotics.ethz.ch/~asl-datasets/ijrr_euroc_mav_dataset/machine_hall/MH_01_easy/MH_01_easy.zip
unzip MH_01_easy.zip -d MH01

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Step 8: Run ORB-SLAM3

Now you’re ready to run ORB-SLAM3.

1. Navigate to the ORB-SLAM3 Folder:

cd ~/Dev/ORB_SLAM3

2. Run the Monocular Example:

./Examples/Monocular/mono_euroc Vocabulary/ORBvoc.txt Examples/Monocular/EuRoC.yaml ~/Datasets/EuRoc/MH01 ./Examples/Monocular/EuRoC_TimeStamps/MH01.txt

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Troubleshooting

1. Error: Missing Dependencies

   • Double-check you’ve installed all required libraries in Step 2.

2. Error: OpenCV Not Found

   • Ensure OpenCV is installed correctly and added to the system’s library path.

3. Build Errors

   • Run the build script (./build.sh) multiple times, as this sometimes resolves errors.

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Additional Resources

• ORB-SLAM3 Official GitHub Repository
• EuRoC MAV Dataset

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This guide should help even beginners install ORB-SLAM3 on Ubuntu. If you encounter issues, feel free to ask for help in the ORB-SLAM3 GitHub issues section or relevant forums.