Franka Emika Robot World Wide Lab Demonstrator

• Documentation: https://llt_dpp.pages.git-ce.rwth-aachen.de/all/franka_wwl_demonstrator/
• Repository: https://git-ce.rwth-aachen.de/llt_dpp/all/franka_wwl_demonstrator

Acknowledgement

• Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germanys Excellence Strategy – EXC-2023 Internet of Production – 390621612

Concept

This project aims to explore the following aspects:

• Data-to-knowledge pipelines within the World Wide Lab
• Automated research data storage and management, especially meta data
• Continous multi-instance dynamics learning for Franka Emika Robot

This project extends the previous work presented by Schneider et al. 2024.

Three instances of Franka Emika Robots are present within the RWTH Aachen University Cluster of Excellence Internet of Production. To generate meaningful knowledge from data gather on these three instances--situtated at the Chair for Laser Technology (LLT), Chair for Machine Tools (WZL MT) and the Institute for Textile Technology (ITA)--automated data storage and management is required. Thus, automated data generation procedures have been implemented and are conducted on each robot instances. Data is automatically tagged with meta data on pushed to NRW RDS by means of RWTH Aachen University meta data platform coscine. This platform both provides the generated data (Trajectory Data resource) as well as imporant metadata such as the source code used for data generation and the universal unique identfier of the robot instance. This data is used to train an inverse dynamics model of the robotic systems. Agents registered to a weight and biases sweep server continously get send new model hyperparameter sets from the sweep server, pull up to date data from NRW RDS and push well performing models back to NRW RDS (Inverse Dynamics Models resource) Train models may be used at the participating institutions fully embracing the Data-to-knowledge pipeline demonstrated within the World Wide Lab.

Setup

This app is contrainerized.

Install docker and docker compose according to sources.

Ensure that incomming traffic is not blocked. Check both ufw and iptables.

FCI requires a RT-Kernel patch. Set it up following their documentation.

Installation

This setup uses docker and docker-compose.

git clone https://git-ce.rwth-aachen.de/llt_dpp/all/franka_wwl_demonstrator
cd franka_wwl_demonstrator

Usage

To start the data generation pipeline run:

docker compose up --build

To stop the pipeline, in a second terminal run:

docker compose down

For detailed / individual usage follow the corresponding readme.