Ubuntu 16.04 下 PL-SLAM (Stereo) 的安装和使用

Overview

欢迎访问 https://cgabc.xyz/posts/b4bebaf6/，持续更新

This code rubengooj/pl-slam contains an algorithm to compute stereo visual SLAM by using both point and line segment features.

• Related Publication

  @article{gomez2017pl,
    title   = {{PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments}},
    author  = {Gomez-Ojeda, Ruben and Zuñiga-Noël, David and Moreno, Francisco-Angel and Scaramuzza, Davide and Gonzalez-Jimenez, Javier},
    journal = {arXiv preprint arXiv:1705.09479},
    year    = {2017}
  

Prerequisites and Dependencies

• Basics

  sudo apt install build-essential pkg-config libboost-dev \
  libsuitesparse-dev libeigen3-dev libyaml-cpp-dev
  

• OpenCV 3.x.x

  • I installed OpenCV 3.3.1 along with ros-kinetic

• G2O

  • recommend version: commit id ff647bd (ff647bd7537860a2b53b3b774ea821a3170feb13)

• MRPT/mrpt: The Mobile Robot Programming Toolkit

  • recommend version: commit id 0c3d605 (0c3d605c3cbf5f2ffb8137089e43ebdae5a55de3)

  git clone https://github.com/MRPT/mrpt.git
  git branch cg_0c3d605 0c3d605c3cbf5f2ffb8137089e43ebdae5a55de3
  git checkout cg_0c3d605
  
  # install dependencies
  sudo apt install libdc1394-22-dev libjpeg-dev libftdi-dev freeglut3-dev \
  libwxgtk3.0-dev zlib1g-dev libusb-1.0-0-dev libudev-dev libfreenect-dev \
  libavformat-dev libswscale-dev libassimp-dev libgtest-dev libpcap-dev
  
  # build & install
  mkdir build & cd build
  cmake .. & make -j4
  sudo make install
  

• rubengooj/stvo-pl: Stereo Visual Odometry by combining point and line segment features

  git clone https://github.com/rubengooj/stvo-pl.git
  cd stvo-pl
  chmod +x build.sh
  ./build.sh
  

Note: it’s better mrpt, stvo-pl and pl-slam are in the same directory

Build

Build pl-slam

git clone https://github.com/rubengooj/pl-slam.git
chmod +x build.sh
./build.sh

Errors

• Q: /usr/bin/ld: cannot find -lg2o_ext_csparse
  A: sudo ln -sv libg2o_csparse_extension.so libg2o_ext_csparse.so

Run

Dataset

• Kitti Dataset: data_odometry_gray (~22G)

Kitti data_odometry_gray

• edit ~/.bashrc, and
  add export DATASETS_DIR=/sequences
• copy pl-slam/config/dataset_params/kitti00-02.yaml
  to /sequences/00/,
  rename the yaml file to dataset_params.yaml and change it if necessary
• source ~/.bashrc
• edit pl-slam/config/config/config_kitti.yaml, change the value of vocabulary_p and vocabulary_l
• run
  ./plslam_dataset 00 -c ../config/config/config_kitti.yaml -o 100 -s 1 -n 1000
  or
  ./plslam_dataset 00 -c ../config/config/config_kitti.yaml -o 100 -s 1

Result

EuRoC MH_01_easy

• edit ~/.bashrc, and add export DATASETS_DIR=
• copy pl-slam/config/dataset_params/euroc_params.yaml to /mav0/,
  rename the yaml file to dataset_params.yaml and change it if necessary
• source ~/.bashrc
• edit pl-slam/config/config/config_euroc.yaml, change the value of vocabulary_p and vocabulary_l
• run ./plslam_dataset mav0 -c ../config/config/config_euroc.yaml -o 100 -s 1

Run Errors

• the app crashed and get the following error when restart the app after close it with Ctrl+C

  DRM_IOCTL_I915_GEM_APERTURE failed: Invalid argument
  Assuming 131072kB available aperture size.
  May lead to reduced performance or incorrect rendering.
  get chip id failed: -1 [22]
  param: 4, val: 0
  Segmentation fault (core dumped)

  and it fixed after reinstalling Nvidia-driver

• the app crashed with the error Segmentation fault (core dumped) after run Frame #1600 with the KITTI data_odometry_gray dataset, but have not solved it