• Journal of Bio-Environment Control
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• v.13 no.1
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• pp.1-7
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• 2004

This study is kinematics for the manipulator development of cucumber harvesting. A theory value was verified by repeated error measurement after the forward kinematics or inverse kinematics analysis of manipulator. Manipulator is consisted of one perpendicular link and two revolution link. The transformation of manipulator can be valued by kinematics using Denavit-Hartenberg parameter. The value of inverse kinematics which is solved by three angles faction shows two types. Repeated errors refered maximum 2.60 mm, 2.05mm and 1.55 mm according to X, Y, Z axis. In this study, the actual coordinates of maximum point and minimum point were agreement in the forward kinematics or inverse kinematics. The results of repeated error measurement were reflect to be smaller compared to a diameter of cucumber. measurement errors were determined by experimented errors during the test. For reducing errors of manipulator and improving work efficiency, the number of link should be reduced and breeding and cultural environment should be considered to reduce the weight and use the hard stuff. The velocity of motor for working should be considered, too.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Composites Research
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• v.35 no.6
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• pp.378-393
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• 2022

As an emerging power generation technology, triboelectric nanogenerators (TENGs) have received increasing attention due to their boundless promise in energy harvesting and self-powered sensing applications. The recent rise of soft robotics has sparked widespread enthusiasm for developing flexible and soft sensors and actuators. TENGs have been regarded as promising power sources for driving actuators and self-powered sensors, providing a unique approach for the development of soft robots with soft sensors and actuators. In this review, TENG-based soft robots with different morphologies and different functions are introduced. Among them, the design of biomimetic soft robots that imitate the structure, surface morphology, material properties, and sensing/generating mechanisms of nature has greatly benefited in improving the performance of TENGs. In addition, various bionic soft robots have been well improved compared to previous driving methods due to the simple structure, self-powering characteristics, and tunable output of TENGs. Furthermore, we provide a comprehensive review of various studies within specific areas of TENG-enabled soft robotics applications. We first explore various recently developed TENG-based soft robots and a comparative analysis of various device structures, surface morphologies, and nature-inspired materials, and the resulting improvements in TENG performance. Various ubiquitous sensing principles and generation mechanisms used in nature and their analogous artificial TENG designs are demonstrated. Finally, biomimetic applications of TENG enabled in tactile displays as well as in wearable devices, artificial electronic skin and other devices are discussed. System designs, challenges and prospects of TENGs-based sensing and actuation devices in the practical application of soft robotics are analyzed.