• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.39-49
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• 1999

This paper describes the development of a vision-aided position and orientation recognition system for automatically adjusting electronic tuners which control the waveform by rotating variable resisters. The position and orientation recognition system estimates the center and the angle of the tuner grooves so that the main controller may correct the difference from the ideal position and thereby manipulate the variable resisters automatically. In this paper a robust algorithm is suggested which estimates the center and the angle of the tuner grooves fast and precisly from the source image with lighting variance and video noise. In the algorithm morphological filtering, 8-chain coding, and invariant moments are sequentially used to figure out image segments concerned. The performance of the proposed system was evaluated using a set of real specimens. The results indicate the system works well enough to be used practically in real manufacturing lines. If the system adopts a high speed frame grabber which enables real time image processing, it can also be applied to positioning of robot manipulators as well as automated PCB adjusters.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.386-391
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• 2015

The mobility of tracked vehicles is mainly influenced by the interaction between the tracks and soil. When the track of a tracked vehicle rotates, there will be a slip effect between the track and the soil, which creates a track shear force and the vehicle’s driving force. In this paper, the modeling of a working tool such as a trenching cutter and a tracked vehicle that is the lower frame of a track-based operating robot was performed. In addition, a numerical simulation was executed to verify the performance of the design objectives and the motion characteristics of the combined system.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.11a
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• pp.105-108
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• 2007

This study aims to develop a performance evaluation system for the Construction Factory(CF). The CF is a kind of full automation system for building construction which consists of the lifting system for building materials, the built-up unit for steel structural components, the bolting robots, the control center for the site management, and the site covering system. The CF is developing now as a project of the construction automation and robotics. In this study we firstly reviewed the state-of-the-art of the construction automation and robotics in the foreign and the domestic, and investigated the precedent case of the CF such as the SMART System of Shimizu Co., Japan. We believe that without an objective evaluation of the results there won't be growth in technological R&D. Therefore, this study sees the developing CF as an new technology and method in building construction, and proposes the direction and frame of the appropriate evaluation which can be applied into the CF.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.10-16
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• 2011

A cabinet is an outer frame of a TV, which is usually made of poly-carbonate. Cabinets are apt to be deformed because of applied heat during injection molding process and UV joining process. Severely deformed cabinets cause a falling-off in quality of the final product. Therefore cabinets should be inspected and only the good ones should be delivered to the following process. We implemented an experimental system for shape recognition of a cabinet and proposed several indices to characterize the shape of a cabinet. We also proposed algorithms to eliminate the possible bias present in measured data and to check the goodness of a cabinet. Experimental results show the feasibility of the propose algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.347-352
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• 2012

This paper presents a robotic foot mechanism based on truss structure for walking robots and analyzes its effectiveness for compliant walking. The specified foot mechanism has been modeled by observing the structure and behavior of human foot. The frame of bone used in the human foot is considered as a truss, and the ligaments of the human foot are represented as a simple stiffness element. So such a robotic foot has an advantage to moderate the impact of foot when a walking robot takes a step. As a result, it is practically expected that the proposed robotic foot mechanism can contribute to reduce the physical fatigue of walking robots.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.51-59
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• 2016

In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.357-362
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• 2019

This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

• International Journal of High-Rise Buildings
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• v.11 no.2
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• pp.115-124
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• 2022

Welding is a significant part of the construction industry. Since most high-rise building construction structures rely on a robust metal frame welded together, welding defect can damage welded structures and is critical to safety and quality. Despite its importance and heavy usage in construction, the labor shortage of welders has been a continuous challenge to the construction industry. To deal with the labor shortage, the ultimate goal of this study is to design and develop an automated robotic welding system composed of a welding machine, unmanned ground vehicle (UGV), robotic arm, and visual sensors. This paper proposes and focuses on automated weaving using the robotic arm. For automated welding operation, a microcontroller is used to control the switch and is added to a welding torch by physically modifying the hardware. Varying weave patterns are mathematically programmed. The automated weaving is tested using a brush pen and a ballpoint pen to clearly see the patterns and detect any changes in vertical forces by the arm during weaving. The results show that the weave patterns have sufficiently high consistency and precision to be used in the actual welding. Lastly, actual welding was performed, and the results are presented.

• Journal of Sensor Science and Technology
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• v.7 no.2
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• pp.124-130
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• 1998

High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three computational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a $64{\times}32$ bit instruction cache and two $1024{\times}32$ bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With $512{\times}512$ pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.