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A real-time, robust and versatile visual-SLAM framework based on deep learning networks

Prerequisites

We have tested the library in Ubuntu 20.04, with the following hardware and software configurations:

  • CPU: Intel Core i7-10700K
  • GPU: NVIDIA GeForce RTX 3080
  • CUDA Version: 11.8

Pangolin

We use Pangolin for visualization and user interface. Dowload and install instructions can be found at: https://github.com/stevenlovegrove/Pangolin.

OpenCV

Required at leat 3.0. Tested with OpenCV 3.4.1.

Eigen3

Required by g2o (see below). Download and install instructions can be found at: http://eigen.tuxfamily.org. Required at least 3.1.0.

ONNXRuntime

Required onnxruntime-linux-x64-gpu-1.16.3 and Modify line 63 of the CmakeLists.txt to the current location of ONNXRuntime library.

ROS (optional)

We provide some examples to process input of a monocular, monocular-inertial, stereo, stereo-inertial or RGB-D camera using ROS. Building these examples is optional. These have been tested with ROS Melodic under Ubuntu 18.04.

Download Examples Folder

Download "Examples" and unzip in ROVER-SLAM/ .

Download Dbow File

Download "voc_binary_tartan_8u_6.zip", and unzip in ROVER-SLAM/Vocabulary/ .

Building Rover-SLAM library and examples

Clone the repository:

git clone https://github.com/zzzzxxxx111/Rover-SLAM.git
cd Rover-slam
mkdir build
cd build
cmake ..
make -j12

Running

Euroc-Monocluar:

./Examples/Monocular/mono_euroc  Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Monocular/EuRoC.yaml /media/xiao/data3/slamdataset/euroc/V202 /media/xiao/data3/learning-slam/Rover-slam/Examples/Monocular/EuRoC_TimeStamps/V202.txt

Euroc-Monocluar-Inerial:

./Examples/Monocular-Inertial/mono_inertial_euroc  Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Monocular-Inertial/EuRoC.yaml /media/xiao/data3/slamdataset/euroc/V203 media/xiao/data3/learning-slam/Rover-slam/Examples/Monocular-Inertial/EuRoC_TimeStamps/V203.txt

TUM-Monocular-Inertial

./Examples/Monocular-Inertial/mono_inertial_tum_vi Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Monocular-Inertial/TUM_512.yaml /media/xiao/data3/slamdataset/dataset-corridor3_512_16/mav0/cam0/data Examples/Monocular-Inertial/TUM_TimeStamps/dataset-corridor3_512.txt Examples/Monocular-Inertial/TUM_IMU/dataset-corridor3_512.txt dataset-corridor3_512_monoi

Euroc-Stereo-Inertial

 ./Examples/Stereo-Inertial/stereo_inertial_euroc /media/xiao/data3/learning-slam/ORB_SLAM3_detailed_comments/Vocabulary/voc_binary_tartan_8u_6.yml.gz Examples/Stereo-Inertial/EuRoC.yaml /media/xiao/data3/slamdataset/euroc/V203 /media/xiao/data3/learning-slam/ORB_SLAM3_detailed_comments/Examples/Stereo/EuRoC_TimeStamps/V203.txt V203_si

The rest of the operations are the same as ORB-SLAM3

Acknowledgments

The completion of this project would not have been possible without the support and contributions of the following open-source projects and tools. We extend our sincere gratitude to:

  1. ORB-SLAM3

  2. AIRVO

  3. SP-Loop

  4. ORB_SLAM3_detailed_comments

  5. SuperPoint_SLAM

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