ERF Workshop & Insight Session 2024: Obtaining Good Data for Agile Production, Logistics and Lab Automation



Dr. Michael Suppa, Roboception GmbH, Germany

Prof. Markus Vincze, Professor, TU Vienna, Austria, confirmed.
Dr. Radhika Gudipati, Ocado Technologies, UK, confirmed.
Dr. Patrick Courtney, CEO, Tec-connection, UK, confirmed.


Perception is one of the key technologies for enabling flexible production, such as pick and place, machine tending, assembly, and quality testing. In order to make use of machine learning and AI in these applications, the question for obtaining good data is becoming more and more relevant. Especially in flexible automation, models of the part are usually available. However, they may represent the final product and not the product as seen in the current production stage. In warehouse logistics and lab automation, the model data if available at all, may be even less reliable.

One of the key findings of previous workshop was the use of synthetic data in combination with real data may be one of the solutions that can address this gap. This workshop will be dedicated to answering the key question on how to address model inaccuracies in new ways to truly enable flexible production. As an outcome, the use and access to good data for three domains will be elaborated to enable end-users, integrators and perception system suppliers to fully exploit and understand the potential of mixed data approaches..


10′ Introduction and definition of key statements/questions, Dr. Michael Suppa, CEO, Roboception GmbH
10′ Towards Tricky (Transparent, Reflective, …) Object Models and Detection, Prof. Markus Vincze, Professor, TU Vienna, Austria
10′ AI-driven perception logistics, Dr. Radhika Gudipati, Ocado Technologies, UK.
10′ Data generation for Lab Automation, Dr. Patrick Courtney, CEO, Tec-connection, UK
10′ The power of synthetic data in Agile Production, Michael Suppa, CEO, Roboception GmbH, Germany
25′ Interactive poll session/round table discussion with the audience
05′ Conclusion and take-home messages

[CLOSED] Insight Session: Call for Contributions

This industrial-driven workshop at the European Robotics Forum (ERF) 2024 in Rimini is followed-by an Insight Session that allows for a deeper insight into the topic. Researchers can present contributions related to cutting-edge research on the topics discussed in the workshop. To foster the interaction, the presentations will be delivered in a ‘pitch and poster’ format.

The goal of this Insight Session is to assess latest technologies and research results on data sets, and the assessment of ground truth data for object classification and pose estimation.

Contributions should address the following topics:

[1] Methods for the generation of synthetic and real data, labelling, and ground truth data for reflective and transparent objects in agile production, logistics and lab automation
[2] Methods for object classification, detection, tracking, reconstruction, depth and accurate pose estimation for automation
[3] Reference data sets for agile production, logistics and lab automation including options for industrial exploitation

Paper format and publication:
Each contribution must be at most 5 pages in the standard Springer Proceedings in Advanced Robotics (SPAR) format. Templates are available at The contributions will be peer-reviewed and all accepted contributions will be indexed. Accepted contributions will be published in the Springer Proceedings in Advanced Robotics (SPAR) with Series Editors Bruno Siciliano, Oussama Khatib.

Papers should be submitted by email: michael.suppa [at]

Important Deadlines:

January 15, 2024: Paper submission deadline
January 22, 2024: Notification of acceptance
February 15, 2024: Final paper submission
March, 13-15, 2024: Presentation during the ERF 2024 in Rimini, Italy ( )

In case of questions and remarks, please reach out to michael.suppa [at]