# hdl_localization

**Repository Path**: leon1128/hdl_localization

## Basic Information

- **Project Name**: hdl_localization
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: BSD-2-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-03
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# hdl_localization
***hdl_localization*** is a ROS package for real-time 3D localization using a 3D LIDAR, such as velodyne HDL32e and VLP16. This package performs Unscented Kalman Filter-based pose estimation. It first estimates the sensor pose from IMU data implemented on the LIDAR, and then performs multi-threaded NDT scan matching between a globalmap point cloud and input point clouds to correct the estimated pose. IMU-based pose prediction is optional. If you disable it, the system predicts the sensor pose with the constant velocity model without IMU information.

Video:<br>
[![hdl_localization](http://img.youtube.com/vi/1EyF9kxJOqA/0.jpg)](https://youtu.be/1EyF9kxJOqA)


## Requirements
***hdl_localization*** requires the following libraries:
- OpenMP
- PCL 1.7

The following ros packages are required:
- pcl_ros
- <a href="https://github.com/koide3/ndt_omp">ndt_omp</a>

## Parameters
All parameters are listed in *launch/hdl_localization.launch* as ros params.<br>
You can specify the initial sensor pose using "2D Pose Estimate" on rviz, or using ros params (see example launch file).

## Example

Example bag files (recorded in an outdoor environment): RE
- [hdl_400.bag.tar.gz](http://www.aisl.cs.tut.ac.jp/databases/hdl_graph_slam/hdl_400.bag.tar.gz) (933MB)

```bash
rosparam set use_sim_time true
roslaunch hdl_localization hdl_localization.launch
```

```bash
roscd hdl_localization/rviz
rviz -d hdl_localization.rviz
```

```bash
rosbag play --clock hdl_400.bag
```

<img src="data/figs/localization1.png" height="256pix" /> <img src="data/figs/localization2.png" height="256pix" /> 

If it doesn't work well, change *ndt_neighbor_search_method* in *hdl_localization.launch* to "DIRECT1". It makes the scan matching significantly fast, but a little bit unstable.

## Related packages

- [interactive_slam](https://github.com/koide3/interactive_slam)
- <a href="https://github.com/koide3/hdl_graph_slam">hdl_graph_slam</a>
- <a href="https://github.com/koide3/hdl_localization">hdl_localization</a>
- <a href="https://github.com/koide3/hdl_people_tracking">hdl_people_tracking</a>

<img src="data/figs/packages.png"/>

Kenji Koide, Jun Miura, and Emanuele Menegatti, A Portable 3D LIDAR-based System for Long-term and Wide-area People Behavior Measurement, Advanced Robotic Systems, 2019 [[link]](https://www.researchgate.net/publication/331283709_A_Portable_3D_LIDAR-based_System_for_Long-term_and_Wide-area_People_Behavior_Measurement).

## Contact
Kenji Koide, k.koide@aist.go.jp

Active Intelligent Systems Laboratory, Toyohashi University of Technology, Japan [\[URL\]](http://www.aisl.cs.tut.ac.jp)  
Robot Innovation Research Center, National Institute of Advanced Industrial Science and Technology, Japan  [\[URL\]](https://unit.aist.go.jp/rirc/en/team/smart_mobility.html)