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DeepGuider

DeepGuider Project is a research project funded by national government. The DeepGuider Project aims to develop a navigation guidance system that enables robots to navigate in urban environment without the need of pre-mapping of the environment. The project was started in April 2019 and is currently under development.

DeepGuider Modules

  • core: Common and basic data structures and interfaces such as pose, path, map, and algorithms
  • map_manager: Map management modules to interact with cloud maps and paths
  • vps: Vision algorithms to find location clues using input images and street-view images (visual positioning system; VPS)
  • localizer: Localization algorithms to estimate accurate robot pose by merging various location clues
  • guidance: Guidance algorithms for the robot to follow the given path and recognize its navigation states
  • exploration: Exploration and recovery algorithms in degenerate cases such as lost

Dependency

  • OpenCV (> 3.0.0, 3-clause BSD License)
    • OpenCV is a base for basic computer vision algorithms, linear algebra, image/video manipulation, and GUI.
  • Python (> 3.6.0, PSF License)
    • Python is utilized by modules such as POI and VPS modules mainly implemented in Python language.
  • QGC Ground Control Station (Apache 2.0 License)
    • UTM-related routines in QGC Ground Control Station is utilized for conversion between geodesic notation (latitude and longitude) and UTM.
    • It is included in EXTERNAL directory.

How to Run Codes

  • Microsoft Windows with Microsoft Visual Studio
  • Linux with GCC
    • Prerequisite
      • GCC and CMake
      • OpenCV: sudo apt install libopencv-dev python3-opencv
      • Python: sudo apt install python3-dev
    • Clone (or unzip) DeepGuider codes at your_folder
    • Run ./setup_all.sh at your_folder/examples/ for initial setup (once at first after downloading)
    • Run ./build_all.sh at your_folder/examples/ for initial setup and build
    • Build an example at your_folder/examples/any_example_to_run: cmake && make
    • Run the executable and enjoy codes

DeepGuider Open Dataset

How to Contribute Your Codes

Please refer CONTRIBUTING.md.

Authors

Please refer AUTHORS.md.

License

Please refer DeepGuider Project LSA.

Acknowledgement

The authors thank the following contributors and projects.

  • This work was supported by the ICT R&D program of MSIT/IITP, Development of AI Technology for Guidance of a Mobile Robot to its Goal with Uncertain Maps in Indoor/Outdoor Environments (2019-0-01309).