scancontext-pybind's Introduction

scancontext-pybind

News

Currently (Apr. 2022), not a set of full features are made yet. For checking the features currently supported, see wrapper.cpp.

Purpose

Goal of this repo is
- For fast python support for lidar-based place recognition
  - ps. the native python version (see https://github.com/gisbi-kim/PyICP-SLAM) was already supported, but it was slow.
- Original C++ code: see https://github.com/irapkaist/scancontext

Build

Please ensure eigen3 is installed (e.g., via sudo apt install libeigen3-dev)
Other dependencies (nanoflann and pybind11) are downloaded automatically (for details, see CMakeLists.txt)

Use the following commands to build:

 $ mkdir build
 $ cd build
 $ cmake ..
 $ make

Install the Python package via pip with

$ cd build
$ make pip-install
# or install manually with
$ cd build/python
$ pip install .

Use examples

For the hands-on exploration of the supported features, for example (you need numpy and open3d),

 $ python3 examples/test_make_desciptor.py
 $ python3 examples/test_compare_scd.py
 $ # to be added ...

Docker support

see docker/docker_run.sh. Modify the REPOSITORY_PATH with your own path.
- For the docker-based test tutorial, see this video (TBA)

Application: PyICP-SLAM2

TBA ...

Cite

  @ARTICLE { gskim-2021-tro,
      AUTHOR = { Giseop Kim and Sunwook Choi and Ayoung Kim },
      TITLE = { Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments },
      JOURNAL = { IEEE Transactions on Robotics },
      YEAR = { 2021 }
  }

  @INPROCEEDINGS { gkim-2018-iros,
    author = {Kim, Giseop and Kim, Ayoung},
    title = { Scan Context: Egocentric Spatial Descriptor for Place Recognition within {3D} Point Cloud Map },
    booktitle = { Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems },
    year = { 2018 },
    month = { Oct. },
    address = { Madrid }
  }