https://github.com/rybandrei2014/obstacle_processor

ROS package for obstacle segmentation in a point cloud scene
https://github.com/rybandrei2014/obstacle_processor

catkin-pkg catkin-workspace cmake cpp kinect kinect-v2 kinectv2 object-detection object-recognition obstacle-detection obstacle-processor obstacle-segmentation rgb-d rgb-d-data ros ros-kinetic ros-node ros-packages segmentation xml

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ROS package for obstacle segmentation in a point cloud scene

• Host: GitHub
• URL: https://github.com/rybandrei2014/obstacle_processor
• Owner: rybandrei2014
• Created: 2018-05-20T18:44:59.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-01-07T20:44:58.000Z (almost 5 years ago)
• Last Synced: 2024-03-21T18:00:12.998Z (9 months ago)
• Topics: catkin-pkg, catkin-workspace, cmake, cpp, kinect, kinect-v2, kinectv2, object-detection, object-recognition, obstacle-detection, obstacle-processor, obstacle-segmentation, rgb-d, rgb-d-data, ros, ros-kinetic, ros-node, ros-packages, segmentation, xml
• Language: C++
• Size: 19.5 KB
• Stars: 14
• Watchers: 0
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Obstacle_processor

ROS package for obstacle segmentation in a point cloud scene.

## Installation

* Before you install the package, you have to configure your RGB-D sensor and calibrate it. You can also run this package offline i.e. streaming point cloud ROS topic from .bag file.

* Clone the repository inside **src/** directory of your catkin workspace

```bash

mkdir obstacle_processor

cd obstacle_processor/

git clone name_of_repository

```

* Run CMake to compile source code

```bash

catkin_make

```

* Source your workspace

```bash

source catkin_ws/devel/setup.bash

```

* Setup your robot platform on a ground and remove the all objects in front of it for calibration purposes and run calibration node

```bash

roslaunch obstacle_processor calibration.launch

```

* Now you can run **obstacle_processor** detection algorithm by either of 5 launch commands (two last commands launch **obstacle_processor_node** along with **kinect2_bridge** package from iai_kinect2 package, but can be replaced for whatever bridge package compatible with your RGB-D sensor that produces point cloud ROS topic)

```bash

roslaunch obstacle_processor obstacle_processor.launch

```

or

```bash

roslaunch obstacle_processor obstacle_processor_rviz.launch

```

or

```bash

roslaunch obstacle_processor obstacle_processor_rviz_debug.launch

```

or

```bash

roslaunch obstacle_processor obstacle_processor_launch_all.launch

```

or

```bash

roslaunch obstacle_processor obstacle_processor_launch_all_rviz.launch

```

## References

The project was done as a part of research during bachelor thesis

### License

MIT

### Citation

If you use the repo in personal project or research, please cite it as follows:

**RYBIN, A. Detekce překážek za použití kamerového 3D skeneru. Brno: Vysoké učení technické v Brně, Fakulta strojního inženýrství, 2018.**

Copyright © 2017 Andrei Rybin