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

本文主要是介绍Ubuntu 16.04 下 PL-SLAM (Stereo) 的安装和使用，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

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=<path-to-data_odometry_gray>/sequences
copy pl-slam/config/dataset_params/kitti00-02.yaml
to <path-to-data_odometry_gray>/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=<path-to-MH_01_easy>
copy pl-slam/config/dataset_params/euroc_params.yaml to <path-to-MH_01_easy>/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