ArticleFoods (Basel, Switzerland)2023
An Evaluation System of Robotic End-Effectors for Food Handling.
Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 15 citations in OpenAlex.
- Automation and Optimization of Food Process Using CNN and Six-Axis Robotic Arm.Foods (Basel, Switzerland) · 2024Article
- An empirical model of soft bellows actuator.Scientific reports · 2024Article
- Evaluation of different robotic grippers for simultaneous multi-object grasping.Frontiers in robotics and AI · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.