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An Evaluation System of Robotic End-Effectors for Food Handling

Zhe Qiu, Hannibal Paul, Zhongkui Wang, Shinichi Hirai, Sadao Kawamura

发表年份
2023
引用次数
18
访问权限
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摘要

Owing to Japan's aging society and labor shortages, the food and agricultural industries are facing a significant demand for robotic food handling technologies. Considering the large variety of food products, available robotic end-effectors are limited. Our primary goal is to maximize the applicability of existing end-effectors and efficiently develop novel ones, and therefore, it is necessary to categorize food products and end-effectors from the viewpoint of robotic handling and establish their relationships through an effective evaluation approach. This study proposes a system for evaluating robotic end-effectors to identify appropriate ones and develop new ones. The evaluation system consists of food categorization based on food properties related to robotic handling, categorization of robotic end-effectors based on their grasping principles, a robotic system with visual recognition based on Robot Operating System 2 (ROS 2) to conduct handling tests, a scoring system for performance evaluation, and a visualization approach for presenting the results and comparisons. Based on food categorization, 14 real food items and their corresponding samples were chosen for handling tests. Seven robotic end-effectors, both commercialized and under development, were selected for evaluation. Using the proposed evaluation system, we quantitatively compared the performance of different end-effectors in handling different food items. We also observed differences in the handling of real food items and samples. The overall performance of an end-effector can be visualized and quantitatively evaluated to demonstrate its versatility in handling various food items.

关键词

Robot end effectorEffectorCategorizationComputer scienceArtificial intelligenceEconomic shortageRobotMachine learning

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