SSL_SLAM3

Lightweight 3-D Localization and Mapping for Solid-State LiDAR (Intel Realsense L515 as an example)

This work provides a basic fusion framework that fuses LiDAR and IMU information to improve the stability performance of SSL_SLAM

If you would like to enable save map and test localization separately, you can check this repo: SSL_SLAM2

This code is an improved implementation of paper "Lightweight 3-D Localization and Mapping for Solid-State LiDAR", accepted in IEEE Robotics and Automation Letters, 2021

A summary video demo can be found at Video

Modifier: Wang Han, Nanyang Technological University, Singapore

1. Solid-State Lidar Sensor Example

1.1 Scene reconstruction

1.2 SFM building example

1.3 Localization and Mapping with L515

2. Prerequisites

2.1 Ubuntu and ROS

Ubuntu 64-bit 18.04.

ROS Noetic. ROS Installation

2.2. Ceres Solver

Follow Ceres Installation.

2.3. PCL

Follow PCL Installation.

Tested with 1.8.1

2.4. Trajectory visualization

For visualization purpose, this package uses hector trajectory sever, you may install the package by

sudo apt-get install ros-noetic-hector-trajectory-server

Alternatively, you may remove the hector trajectory server node if trajectory visualization is not needed

3. Build

3.1 Clone repository:

    cd ~/catkin_ws/src
    git clone https://github.com/wh200720041/ssl_slam3.git
    cd ..
    catkin_make
    source ~/catkin_ws/devel/setup.bash

3.2 Download test rosbag

You may download our recorded data (7.8GB) if you dont have realsense L515, and by defult the file should be under home/user/Downloads unzip the file

cd ~/Downloads
unzip ~/Downloads/library.zip

3.3 Launch ROS

    roslaunch ssl_slam3 ssl_slam3.launch

4. Sensor Setup

If you have new Realsense L515 sensor, you may follow the below setup instructions

4.1 IMU calibration (optional)

You may read official document [L515 Calibration Manual] (https://github.com/l515_calibration_manual.pdf) first

use the following command to calibrate imu, note that the build-in imu is a low-grade imu, to get better accurate, you may use your own imu

cd ~/catkin_ws/src/ssl_slam3/l515_imu_calibration
python rs-imu-calibration.py

4.2 L515

4.3 Librealsense

Follow Librealsense Installation

4.4 Realsense_ros

Copy realsense_ros package to your catkin folder

    cd ~/catkin_ws/src
    git clone https://github.com/IntelRealSense/realsense-ros.git
    cd ..
    catkin_make

4.5 Launch ROS

Make Lidar still for 1 sec to estimate the initial bias, otherwise will cause localization failure!

    roslaunch ssl_slam3 ssl_slam3_L515.launch

5. Citation

If you use this work for your research, you may want to cite the paper below, your citation will be appreciated

@article{wang2021lightweight,
  author={H. {Wang} and C. {Wang} and L. {Xie}},
  journal={IEEE Robotics and Automation Letters}, 
  title={Lightweight 3-D Localization and Mapping for Solid-State LiDAR}, 
  year={2021},
  volume={6},
  number={2},
  pages={1801-1807},
  doi={10.1109/LRA.2021.3060392}}

dodeakim / ssl_slam3