BinRoot/Fluent-Extractor

Learning Human Utility from Video Demonstrations for Deductive Planning in Robotics (CoRL 2017)

Intro

This is the official repository for the paper Learning Human Utility from Video Demonstrations for Deductive Planning in Robotics (CoRL 2017). We are cleaning up the code and documentation. Please stay tuned.

If you use this code, please cite:

@inproceedings{shukla17,
  title={Learning Human Utility from Video Demonstrations for Deductive Planning in Robotics},
  author={Shukla, Nishant and He, Yunzhong and Chen, Frank and Zhu, Song-Chun},
  booktitle={The Conference on Robot Learning (CoRL)},
  year={2017}
}

Overview of system

There are 2 nodes:

1. fluent_extractor: Subscribes to vision_buffer_pcl and extracts pointcloud features
2. vision_buffer: Publishes cloth pointcloud to vision_buffer_pcl

Setup

1. Install dependencies

Install pcl_ros as well as pcl

• Install pcl_ros in Kinetic: sudo apt-get install ros-kinetic-pcl-ros
• Install pcl in Ubuntu 16.04: https://larrylisky.com/2016/11/03/point-cloud-library-on-ubuntu-16-04-lts/
• Install cv_bridge by sudo apt-get install ros-kinetic-cv-bridge

2. Follow steps 1-3 http://sdk.rethinkrobotics.com/wiki/Workstation_Setup

Install the appropriate ROS version. Kinectic works on Ubuntu 16.04, whereas Indigo works on Ubuntu 14.04.

3. Put this fluent_extractor code in ros_ws/src/. Then run the following (and resolve build errors by installing required libraries):

    $ catkin_make
   

4. Edit the config.json file located ros_ws/src/fluent_extractor.

5. Start the fluent_extractor

    $ rosrun fluent_extractor fluent_extractor
   

6. Run the vision_buffer

    $ rosrun fluent_extractor vision_buffer src/fluent_extractor/config.json