Dr. Michael Suppa, Roboception GmbH, Germany
Prof. Markus Vincze, TU Vienna, Austria
Radhita Gudipati, Ocado Technology, UK
Dr. Patrick Courtney, Tec-connection, UK
Motivation and Objectives:
Perception is one of the key technologies for enabling flexible production, such as pick and place, machine tending, assembly, and quality testing. 3 major trends can be observed.
GOOD DATA, NOT BIG DATA: Synthetic data generation based on model data and enriched by real data create realistic ground-truth training data sets for machine learning.
PLUG-AND-PRODUCE: The perception component of an automation solution must be easily adjustable to changing requirements.
EASE-OF-USE: With robot vision expertise being a scarce resource, usability for robot users with little to now vision knowledge is a game-changer.
These trends increase the flexibility making the RoI much easier to demonstrate, especially for SMEs. The data requirements for industrial use cases are elaborated in an interactive session with the attendees guided by three key questions. The goal is to enable flexible production.
11:05 Introduction and definition of key statements/questions, Dr. Michael Suppa, Roboception GmbH
11:15 Towards Detecting and Grasping Transparent Objects, Prof. Markus Vincze, TU Vienna, Austria
11:25 Ocado Bot data orchestrations, Radhita Gudipati, Ocado Technology, UK
11:35 Data generation for Lab Automation, Dr. Patrick Courtney, Tec-connection, UK
11:45 Good Data for pick-and-place in Agile Production, Dr. Michael Suppa, Roboception GmbH, Germany
11:55 Interactive Poll Session/ Round Table Discussion
12:20 Conclusion and take home messages
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