3D Track

Application goals

  • Integrate a virtual 3D sensor into the existing open source project assembly.

  • Detect obstacles, workpieces, human hands, or the robot itself in the point clouds.

Required team skills

  • JavaScript
  • 3D Computer Vision
  • Machine Learning (optional)

Resources

ASSEMBLY Robot Simulator
ASSEMBLY GitHub Repository
Time-of-Flight Image Sensing @ Infineon
Time-of-Flight Image Sensing @ pmd

Prerecorded data of manufacturing-related scenes, which also include human operators will be provided.

Within the CoMeMak project TU Wien has created ASSEMBLY, an online robot simulator. The open source code for the simulator is available at GitHub and is ideally suited for virtual hackathons.

Experiment with the robot arm, explore the code and develop new application ideas! The code will remain accessible within GitHub so you can continue working on your idea even after the Hackathon is over.

The first task in this track is to implement a simple simulator for 3D sensors that can be placed in the simulated environment. This shall give the arm the ability see in 3D and to become aware of its environment, enabling complex interaction with objects, other robots and even human operators.

Show your creativity by implementing innovative new applications using the 3D sensor! Detect objects, avoid obstacles, interact with human operators or create your own application idea!

Outcome

Track Credits

Marcus Hennecke (Infineon)

Univ.-Prof. Sebastian Schlund (TU Wien)

David Kostolani (TU Wien)

Univ.-Prof. Dr.-Ing. Sebastian Schlund is BMK Endowed Professor for Industry 4.0 at TU Wien, where he heads the Human-Machine Interaction research area at the Institute of Management Sciences (IMW). With this endowed professorship, the TU Vienna is focusing on the area of Cyber Physical Production and Assembly Systems with a focus on research and development of the interoperability of technology, people and organisation.

Track Partner