Development of Fishcake Gripping and Classification Automation Process Based on Suction Shape Transformation Gripper

The surge in demand for automating seafood processing necessitates the development of robotic processes for transportation, packaging, and classification. South Korean companies are actively constructing diverse robots and grippers for fishcake handling, yet small workshops face spatial constraints. To address this, the study focuses on creating a gripper capable of versatile fishcake handling within compact spaces. The gripper, designed for single-robot use, employs three suction cups, adapting its grip based on fishcake shapes. Small fishcakes are gripped at the center with one suction cup, elongated ones with two cups aligned to the slope, and wider ones with three cups. A testbed with the gripper attached to a robot facilitates fishcake gripping, classification, and automation testing. Fishcake recognition and gripping tests revealed challenges based on shape, width, and material. Despite difficulties, a commendable 100% success rate was achieved for the majority of fishcakes, showcasing the gripper’s effectiveness. Identified improvements include reducing the suction cup diameter and increasing pressure for enhanced gripping and classification in confined spaces. The study demonstrates the successful development of a gripper for versatile fishcake handling, particularly beneficial for small workshops. The identified improvements offer pathways to enhance efficiency in fishcake gripping and classification within limited spaces

Development of rotary hydro-elastic actuator with robust internal-loop-compensator-based torque control and cross-parallel connection spring

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Top-Gate Field-Effect Transistor as a Testbed for Evaluating the Photostability of Organic Photovoltaic Polymers

© 2022 Wiley-VCH GmbHLight-induced performance degradation in organic solar cells (OSCs) is a major impediment to their commercialization. As the photostability of OSCs strongly depends on the material's properties, the most effective solution for this concern is to develop a photostable material. However, the wide variety of causes of photo-instability in a standard multilayered OSC structure complicates the evaluation of photostability of newly developed materials. To address this challenge, a top-gate field-effect transistor (FET) as a testbed for evaluating the photostability of OSC materials is proposed. This device test platform minimizes the internal and external origins of photo-instability by employing a fluoropolymer gate dielectric. The photostability of an OSC material incorporated in this FET testbed can be evaluated by monitoring light-induced mobility degradation. Two types of common donor polymers with similar chemical structures and crystallinity are employed as test materials, and their photostability is evaluated. The test results correspond to the photostability measurements conducted in the standard OSC structure, validating the proposed FET testbed. The proposed FET testbed enables rapid evaluation of the photostability of a newly developed OSC material, thereby providing timely feedback to material scientists. This boosts the development of photostable OSC materials.N

Pipe Spatter Detection and Grinding Robot

This paper proposes a robotic system that automatically identifies and removes spatters generated while removing the back-bead left after the electric resistance welding of the outer and inner surfaces during pipe production. Traditionally, to remove internal spatters on the front and rear of small pipes with diameters of 18–25 cm and lengths of up to 12 m, first, the spatter locations (direction and length) are determined using a camera that is inserted into the pipe, and then a manual grinder is introduced up to the point where spatters were detected. To optimize this process, the proposed robotic system automatically detects spatters by analyzing the images from a front camera and removes them, using a grinder module, based on the spatter location and the circumferential coordinates provided by the detection step. The proposed robot can save work time by reducing the required manual work from two points (the front and back of the pipe) to a single point. Image recognition enables the detection of spatters with sizes between 0.1 and 10 cm with 94% accuracy. The internal average roughness, Ra, of the pipe was confirmed to be 1 µm or less after the spatters were finally removed

Pipe Spatter Detection and Grinding Robot

This paper proposes a robotic system that automatically identifies and removes spatters generated while removing the back-bead left after the electric resistance welding of the outer and inner surfaces during pipe production. Traditionally, to remove internal spatters on the front and rear of small pipes with diameters of 18–25 cm and lengths of up to 12 m, first, the spatter locations (direction and length) are determined using a camera that is inserted into the pipe, and then a manual grinder is introduced up to the point where spatters were detected. To optimize this process, the proposed robotic system automatically detects spatters by analyzing the images from a front camera and removes them, using a grinder module, based on the spatter location and the circumferential coordinates provided by the detection step. The proposed robot can save work time by reducing the required manual work from two points (the front and back of the pipe) to a single point. Image recognition enables the detection of spatters with sizes between 0.1 and 10 cm with 94% accuracy. The internal average roughness, Ra, of the pipe was confirmed to be 1 µm or less after the spatters were finally removed