Sai Preetham Sata, Benjamin Noack, Markus Weidmann, Sebastian Frasch, Michael Albrecht, Andreas Scholz, Hanna Westphal, Elmar Woschke, Matthias Pusch, André Katterfeld
Comparison of Tracking Performance of Multiple Objects on a Peristaltic Conveyor System (accepted) Proceedings of the 23rd IFAC World Congress (IFAC 2026), Busan, South Korea, August, 2026.
BibTeX
@inproceedings{IFAC26_Sata,
title = {{Comparison of Tracking Performance of Multiple Objects on a Peristaltic Conveyor System (accepted)}},
author = {Sai Preetham Sata and Benjamin Noack and Markus Weidmann and Sebastian Frasch and Michael Albrecht and Andreas Scholz and Hanna Westphal and Elmar Woschke and Matthias Pusch and Andr{\'e} Katterfeld},
booktitle = {Proceedings of the 23rd IFAC World Congress (IFAC 2026)},
address = {Busan, South Korea},
month = aug,
year = {2026}
}
Sai Preetham Sata, Markus Weidmann, Sebastian Frasch, Michael Albrecht, Benjamin Noack, Andreas Scholz
Detection and Instance Segmentation of Polybags for Accurate Parameter Estimation (accepted) Proceedings of the 2026 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2026), Genova, Italy, June, 2026.
BibTeX
@inproceedings{AIM26_Sata,
title = {{Detection and Instance Segmentation of Polybags for Accurate Parameter Estimation (accepted)}},
author = {Sai Preetham Sata and Markus Weidmann and Sebastian Frasch and Michael Albrecht and Benjamin Noack and Andreas Scholz},
booktitle = {Proceedings of the 2026 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2026)},
address = {Genova, Italy},
month = jun,
year = {2026}
}
Sai Preetham Sata, Markus Weidmann, Sebastian Frasch, Michael Albrecht, Hanna Westphal, Matthias Pusch, Benjamin Noack, Andreas Scholz, Elmar Woschke, André Katterfeld
Identification and Tracking of Multiple Objects on a Peristaltic Conveyor System Proceedings of the 5th International Conference on Robotics, Automation, and Artificial Intelligence (RAAI 2025), Singapore, December, 2025.
The courier express parcel industry has demonstrated considerable volumetric growth in shipment activity throughout the preceding years. In order to enhance the performance and throughput of the material flow technology without compromising on space requirements at distribution centers, various methods are being developed, and their feasibility is being investigated. One such method includes the development of a robust object identification system that is able to identify and track objects for longer duration. Artificial intelligence based methods that utilize You Only Look Once (YOLO) deep learning architecture have been shown to reliably detect and identify objects in several applications provided that there is enough high-quality training data. The aim of this work is to detect and track multiple objects on the Peristaltic Conveyor System (PCS) using YOLO-based detection along with existing tracking algorithms, and to estimate the real-time location and dimensions of these objects. The reliability of the detection and tracking approaches is evaluated by comparing their performance using appropriate detection and tracking metrics.
@inproceedings{RAAI25_Sata,
title = {{Identification and Tracking of Multiple Objects on a Peristaltic Conveyor System}},
author = {Sai Preetham Sata and Markus Weidmann and Sebastian Frasch and Michael Albrecht and Hanna Westphal and Matthias Pusch and Benjamin Noack and Andreas Scholz and Elmar Woschke and Andr{\'e} Katterfeld},
booktitle = {Proceedings of the 5th International Conference on Robotics, Automation, and Artificial Intelligence (RAAI 2025)},
address = {Singapore},
doi = {10.1109/RAAI67517.2025.11423122},
month = dec,
year = {2025}
}
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