# linefit
**Repository Path**: kin-zhang/linefit
## Basic Information
- **Project Name**: linefit
- **Description**: 适用于无人驾驶的地面分割算法
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-04-28
- **Last Updated**: 2024-04-28
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
linefit
---
linefit is a ground segmentation algorithm for 3D point clouds. This repo we setup a python binding for the original C++ code and push to pypi for easy installation through `pip install linefit`.
Author: C++ code from [Lorenz Wellhausen](https://github.com/lorenwel), nanobind by [Qingwen Zhang](https://kin-zhang.github.io/).
Running on macOS, Windows and Linux, with Python Version >= 3.8.
Available in: 
## 0. Setup
Choose one of the following options to install the package (recommended to use Option A `pip install linefit`):
Option A: Install from pypi `pip install linefit`
Option B: Clone this repo and run following to build:
```bash
cmake -B build && cmake --build build
pip install .
python3 -c 'import linefit; print("success")'
```
## 1. Run the example
After installation, you can run the example by, it will directly show a default effect of demo data.
```bash
python example.py
```
A window will pop up and show the ground segmentation result.
## Parameter description
TL;DR: tune the `sensor_height` to offset the ground point z to `0`. Others are optional for better performance. If you are interested in the details, please read the following.
Parameters are set in `assets/config.toml`
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.
### 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.
## Acknowledgement & Citation
The original C++ code is from [the repo we forked: lorenwel/linefit_ground_segmentation](https://github.com/lorenwel/linefit_ground_segmentation).
The original methods are described in the following paper:
```
@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}
}
```
More python binding examples can be found in our other project:
- [dufomap](https://github.com/KTH-RPL/dufomap): a dynamic awareness mapping framework. Remove dynamic points in a raw map.
- [dztimer](https://github.com/KTH-RPL/dztimer): a breakout timer for python code.