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https://github.com/lorenwel/linefit_ground_segmentation

Ground Segmentation from Lidar Point Clouds
https://github.com/lorenwel/linefit_ground_segmentation

lidar ros segmentation

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Ground Segmentation from Lidar Point Clouds

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# linefit_ground_segmentation



Implementation of the ground segmentation algorithm proposed in 

```

@inproceedings{himmelsbach2010fast,

  title={Fast segmentation of 3d point clouds for ground vehicles},

  author={Himmelsbach, Michael and Hundelshausen, Felix V and Wuensche, H-J},

  booktitle={Intelligent Vehicles Symposium (IV), 2010 IEEE},

  pages={560--565},

  year={2010},

  organization={IEEE}

}

```

The `linefit_ground_segmentation` package contains the ground segmentation library.

A ROS interface is available in `linefit_ground_segmentation_ros` 



The library can be compiled separately from the ROS interface if you're not using ROS.



## Installation



Requires the following dependencies to be installed:



- *catkin_simple* `https://github.com/catkin/catkin_simple.git` 

- *eigen_conversions* `sudo apt install ros-noetic-eigen-conversions`



Compile using your favorite catkin build tool (e.g. `catkin build linefit_ground_segmentation_ros`)



## Launch instructions



The ground segmentation ROS node can be launch by executing `roslaunch linefit_ground_segmentation_ros segmentation.launch`.

Input and output topic names can be specified in the same file.



Getting up and running with your own point cloud source should be as simple as:



1. Change the `input_topic` parameter in `segmentation.launch` to your topic.

2. Adjust the `sensor_height` parameter in `segmentation_params.yaml` to the height where the sensor is mounted on your robot (e.g. KITTI Velodyne: 1.8m)



## Parameter description



Parameters are set in `linefit_ground_segmentation_ros/launch/segmentation_params.yaml`



This algorithm works on the assumption that you known the height of the sensor above ground. 

Therefore, **you have to adjust the `sensor_height`** to your robot specifications, otherwise, it will not work.



The default parameters should work on the KITTI dataset.



### Ground Condition

- **sensor_height**  Sensor height above ground.

- **max_dist_to_line**  maximum vertical distance of point to line to be considered ground.

- **max_slope**  Maximum slope of a line.

- **min_slope**  Minimum slope of a line.

- **max_fit_error**  Maximum error a point is allowed to have in a line fit.

- **max_start_height**  Maximum height difference between new point and estimated ground height to start a new line.

- **long_threshold**  Distance after which the max_height condition is applied.

- **max_height**  Maximum height difference between line points when they are farther apart than *long_threshold*.

- **line_search_angle**  How far to search in angular direction to find a line. A higher angle helps fill "holes" in the ground segmentation.

- **gravity_aligned_frame**  Name of a coordinate frame which has its z-axis aligned with gravity. If specified, the incoming point cloud will be rotated, but not translated into this coordinate frame. If left empty, the sensor frame will be used.



### Segmentation



- **r_min**  Distance at which segmentation starts.

- **r_max**  Distance at which segmentation ends.

- **n_bins**  Number of radial bins.

- **n_segments**  Number of angular segments.



### Other



- **n_threads**  Number of threads to use.

- **latch**  Latch output point clouds in ROS node. 

- **visualize** Visualize the segmentation result. **ONLY FOR DEBUGGING.** Do not set true during online operation.