Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/174610
Title: | A bin-picking benchmark for systematic evaluation of robotic-assisted food handling for line production | Authors: | Zhu, Guoniu Zeng, Yadan Teoh, Yee Seng Toh, Elvin Wong, Choon Yue Chen, I-Ming |
Keywords: | Engineering | Issue Date: | 2023 | Source: | Zhu, G., Zeng, Y., Teoh, Y. S., Toh, E., Wong, C. Y. & Chen, I. (2023). A bin-picking benchmark for systematic evaluation of robotic-assisted food handling for line production. IEEE/ASME Transactions On Mechatronics, 28(3), 1778-1788. https://dx.doi.org/10.1109/TMECH.2022.3227038 | Project: | M21K1a0104 1822500053 |
Journal: | IEEE/ASME Transactions on Mechatronics | Abstract: | Robotic manipulation and automation have gained increasing popularity in the food manufacturing industry due to their potential benefits for enhancing hygiene standards, enforcing quality consistency, promoting product traceability, and reducing labor costs. As a majority of robotic manipulation, the pick-and-place operation plays a crucial role in food handling applications. However, the reproducibility and comparability of results have put a dilemma that hinders further advancement in this field, especially for those unstructured scenarios. To tackle such thorny issues, this article proposes a benchmarking framework for system-level evaluation of robotic-assisted food handling under the line production environment. A typical food handling scenario, including a pick-and-place operation and a packing operation, is presented as the benchmark task, where food items are supposed to be picked from the tray and placed in the serving dish. A robotic system incorporating a high-speed Delta robot, vision system, conveyor belt, and end-effector is developed as the testbed for the benchmarking implementation. Finally, five variants of the robotic system with different end-effectors are evaluated using the proposed benchmarking framework. Comparative studies illustrate the performance of various benchmarked systems and validate the applicability of the benchmarking strategy for the food handling context. Videos of our experiments are available at https://youtu.be/SBAOoswnjWM. | URI: | https://hdl.handle.net/10356/174610 | ISSN: | 1083-4435 | DOI: | 10.1109/TMECH.2022.3227038 | Schools: | School of Mechanical and Aerospace Engineering | Research Centres: | Robotics Research Centre | Rights: | © 2022 IEEE. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | MAE Journal Articles |
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