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https://github.com/wh200720041/floam

Fast LOAM: Fast and Optimized Lidar Odometry And Mapping for indoor/outdoor localization IROS 2021
https://github.com/wh200720041/floam

aloam loam localization robotics slam

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Fast LOAM: Fast and Optimized Lidar Odometry And Mapping for indoor/outdoor localization IROS 2021

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# FLOAM 

## Fast LOAM (Lidar Odometry And Mapping)



This work is an optimized version of A-LOAM and LOAM with the computational cost reduced by up to 3 times.

This code is modified from [LOAM](https://github.com/laboshinl/loam_velodyne) and [A-LOAM](https://github.com/HKUST-Aerial-Robotics/A-LOAM) .



**Modifier:** [Wang Han](http://wanghan.pro), Nanyang Technological University, Singapore



## 1. Demo Highlights

Watch our demo at [Video Link](https://youtu.be/PzZly1SQtng)












## 2. Evaluation

### 2.1. Computational efficiency evaluation

Computational efficiency evaluation (based on KITTI dataset):

Platform: Intel® Core™ i7-8700 CPU @ 3.20GHz 

| Dataset                                      | ALOAM                      | FLOAM                  |

|----------------------------------------------|----------------------------|------------------------|

| `KITTI`                                      | 151ms                      | 59ms                   |



Localization error:

| Dataset                                      | ALOAM                      | FLOAM                  |

|----------------------------------------------|----------------------------|------------------------|

| `KITTI sequence 00`                          | 0.55%                      | 0.51%                  |

| `KITTI sequence 02`                          | 3.93%                      | 1.25%                  |

| `KITTI sequence 05`                          | 1.28%                      | 0.93%                  |



### 2.2. localization result








### 2.3. mapping result












## 3. Prerequisites

### 3.1 **Ubuntu** and **ROS**

Ubuntu 64-bit 18.04.



ROS Melodic. [ROS Installation](http://wiki.ros.org/ROS/Installation)



### 3.2. **Ceres Solver**

Follow [Ceres Installation](http://ceres-solver.org/installation.html).



### 3.3. **PCL**

Follow [PCL Installation](http://www.pointclouds.org/downloads/linux.html).



### 3.4. **Trajectory visualization**

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

```

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

```

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



## 4. Build 

### 4.1 Clone repository:

```

    cd ~/catkin_ws/src

    git clone https://github.com/wh200720041/floam.git

    cd ..

    catkin_make

    source ~/catkin_ws/devel/setup.bash

```

### 4.2 Download test rosbag

Download [KITTI sequence 05](https://drive.google.com/file/d/1eyO0Io3lX2z-yYsfGHawMKZa5Z0uYJ0W/view?usp=sharing) or [KITTI sequence 07](https://drive.google.com/file/d/1_qUfwUw88rEKitUpt1kjswv7Cv4GPs0b/view?usp=sharing)



Unzip compressed file 2011_09_30_0018.zip. If your system does not have unzip. please install unzip by 

```

sudo apt-get install unzip 

```



And this may take a few minutes to unzip the file

```

	cd ~/Downloads

	unzip ~/Downloads/2011_09_30_0018.zip

```



### 4.3 Launch ROS

```

    roslaunch floam floam.launch

```

if you would like to create the map at the same time, you can run (more cpu cost)

```

    roslaunch floam floam_mapping.launch

```

If the mapping process is slow, you may wish to change the rosbag speed by replacing "--clock -r 0.5" with "--clock -r 0.2" in your launch file, or you can change the map publish frequency manually (default is 10 Hz)



## 5. Test on other sequence

To generate rosbag file of kitti dataset, you may use the tools provided by 

[kitti_to_rosbag](https://github.com/ethz-asl/kitti_to_rosbag) or [kitti2bag](https://github.com/tomas789/kitti2bag) 



## 6. Test on Velodyne VLP-16 or HDL-32

You may wish to test FLOAM on your own platform and sensor such as VLP-16

You can install the velodyne sensor driver by 

```

sudo apt-get install ros-melodic-velodyne-pointcloud

```

launch floam for your own velodyne sensor

```

    roslaunch floam floam_velodyne.launch

```

If you are using HDL-32 or other sensor, please change the scan_line in the launch file 



## 7.Acknowledgements

Thanks for [A-LOAM](https://github.com/HKUST-Aerial-Robotics/A-LOAM) and LOAM(J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time) and [LOAM_NOTED](https://github.com/cuitaixiang/LOAM_NOTED).



## 8. Citation

If you use this work for your research, you may want to cite

```

@inproceedings{wang2021,

  author={H. {Wang} and C. {Wang} and C. {Chen} and L. {Xie}},

  booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 

  title={F-LOAM : Fast LiDAR Odometry and Mapping}, 

  year={2020},

  volume={},

  number={}

}

```