Cagatay Odabasi — accepted AI-conference papers

2026

Efficient Real-World Benchmarking for Practical Fine-Grained Product Identification in Retail Robotics for Picking and Stock Taking

Jochen Lindermayr, Florian Jordan, Cagatay Odabasi, Werner Kraus, Richard Bormann, Marco F. Huber

ICRA 2026poster

The rapid evolution of retail robotics is set to transform in-store operations through advanced automation, spanning vision-based inventory tracking, order picking, packing, and restocking. Yet fine-grained product identification remains a bottleneck: assortments change, packaging evolves, and shelv…

Cited by 0 Scholar ↗

2023

IPA-3D1K: A Large Retail 3D Model Dataset for Robot Picking

Jochen Lindermayr, Cagatay Odabasi, Florian Jordan, Florenz Graf, Lukas Knak, Werner Kraus +2

IROS 2023poster

Robotic applications like automated order picking in warehouses or retail stores, or fetch and carry tasks in hospitals, care homes, or households rely on the capability of service robots to find and handle a specific type of object. These applications are challenging as the set of objects is very l…

Cited by 4 Source ↗Scholar ↗