• Journal of Biosystems Engineering
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• v.26 no.3
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• pp.253-262
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• 2001

This study was conducted to develop the vision system of a robotic transplanter for plug-seedling. A color image processing algorithm was developed to identify and locate empty cells and bad plants in the seedling tray. The image of pepper and tomato seedling tray was segmented into regions of plants, frame and soil using threshold technique which utilized Q of YIQ for finding leaves and H of HSI for finding frame of tray in the color coordinate system. The recognition system was able to successfully identify empty cells and bad seeding and locate their two-dimensional locations. The overall success rate of the recognition system was about 99%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.254-258
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• 1996

In this paper, we proposed realtime visual tracking system of moving object for 2D target using extended Kalman Filter Algorithm. A targeting marker are recongnized in each image frame and positions of targer object in each frame from a CCD camera while te targeting marker is attached to the tip of the SCARA robot hand. After the detection of a target coming into any position of the field-of-view, the target is tracked and always made to be located at the center of target window. Then, we can track the moving object which moved in inter-frames. The experimental results show the effectiveness of the Kalman filter algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.266-273
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• 2024

With the rising interaction between robots and humans, detecting collisions has become increasingly vital for ensuring safety. In this paper, we propose a novel approach for detecting collisions without using force torque sensors or tactile sensors, utilizing a Transformer-based neural network architecture. The proposed collision detection approach comprises a torque estimator network that predicts the joint torque in a free-motion state using Synchronous time-step encoding, and a collision discriminator network that predicts collisions by leveraging the difference between estimated and actual torques. The collision discriminator finally creates a binary tensor that predicts collisions frame by frame. In simulations, the proposed network exhibited enhanced collision detection performance relative to the other kinds of networks both in terms of prediction speed and accuracy. This underscores the benefits of using Transformer networks for collision detection tasks, where rapid decision-making is essential.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.390-397
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• 2019

A mechanical model of band sawing saw frame was established according to an analysis of a commonly used saw-frame structure diagram to overcome the problems of low service life, substandard cutting precision and efficiency, and high manufacturing cost caused by the unreasonable design of saw frame. Taking a particular type of sawing machine as an example, stress cycle analysis of the saw blade was carried out according to the mechanical model of the saw frame, and the fatigue analysis model of the most dangerous cross-section point that was most prone to fatigue failure of the saw blade was then established. The fatigue analysis result was used as the basis for the improved design of the saw frame, and the improved detailed saw-frame design parameters were obtained. The results suggested that the saw frame system is much more compact and the saw blade force met the fatigue strength requirements through the improved design. In addition, the service life of the saw blade and the cutting precision were increased. The established mechanical model of the saw frame in this paper is used widely and has high practical application values.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.88-96
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• 2011

Underwater acoustic communication is applicable in various areas, such as ocean data collection, undersea exploration and development, tactical surveillance, etc. Thus, robot control system construction used for underwater-robot like AUV or ROV is essential in these areas. In this paper, we propose the Message Merging MAC($M^2$-MAC) protocol, which is suitable for real time robot control system, considering energy efficiency in important parts of underwater acoustic sensor network constitution. In this proposed MAC protocol, gateway node receives the data from robot nodes according to the time slots that were allotted previously. And messages delivered from base-station are generated to one MAC frame by buffering process. Finally, generated MAC frames are broadcasted to all robot nodes in the cluster. Our suggested MAC protocol can also be hybrid MAC protocol, which is successful blend of contention based and contention-free based protocol through relevant procedure with Maintenance&Sleep (M&S) period, when new nodes join and leave as an orphan. We propose mathematical analysis model concerned about End-to-End delay and energy consumption, which is important factor in constructing real-time robot control system. We also verify the excellence of performance according to comparison of existing MAC protocols with our scheme.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.2
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• pp.178-184
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• 2012

This paper presents a transformable track mechanism for wall climbing robots. The proposed mechanism allows a wall climbing robot to go over obstacles by transforming the track shape, and also increases contact area between track and wall surface for safe attachment. The track mechanism is realized using a timing belt track with one driving actuator. The inner frame of the track consists of serially connected 5R-joints and 1P-joint, and all joints of the inner frame are passively operated by springs, so the mechanism does not require any actuators and complex control algorithms to change its shape. Static analysis is carried out to determine design parameters which enable $90^{\circ}$ wall-to-wall transition and driving over projected obstacles on wall surfaces. A Prototype is manufactured using the transformable track on which polymer magnets are installed for adhesion force. The size of the prototype is $628mm{\times}200mm{\times}150mm$ ($Length{\times}Width{\times}Height$) and weight is 4kgf. Experiments are performed to verify its climbing capability focusing on $90^{\circ}$ wall to wall transition and driving over projected obstacle.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.33-44
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• 2010

This paper propose the structure of real-time face detection hardware architecture for robot vision processing applications. The proposed architecture is robust against illumination changes and operates at no less than 60 frames per second. It uses Modified Census Transform to obtain face characteristics robust against illumination changes. And the AdaBoost algorithm is adopted to learn and generate the characteristics of the face data, and finally detected the face using this data. This paper describes the face detection hardware structure composed of Memory Interface, Image Scaler, MCT Generator, Candidate Detector, Confidence Comparator, Position Resizer, Data Grouper, and Detected Result Display, and verification Result of Hardware Implementation with using Virtex5 LX330 FPGA of Xilinx. Verification result with using the images from a camera showed that maximum 32 faces per one frame can be detected at the speed of maximum 149 frame per second.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2400-2405
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• 2013

We detect the obstacle for the UGV(unmanned ground vehicle) from the compound image which is generated by stereo vision sensor masking the depth image and color image. Stereo vision sensor can gathers the distance information by stereo camera. The obstacle information from the depth compound image can be send to mobile robot and the robot can localize the indoor area. And, we test the performance of the mobile robot in terms of distance between the obstacle and the robot's position and also test the color, depth and compound image respectively. Moreover, we test the performance in terms of number of frame per second which is processed by operating machine. From the result, compound image shows the improved performance in distance and number of frames.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1605-1614
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• 2009

The technique of simultaneous localization and mapping is the most important research topic in mobile robotics. In the process of building a map in its available memory, the robot memorizes environmental information on the plane of grid or topology. Several approaches about this technique have been presented so far, but most of them use mapping technique as either grid-based map or topology-based map. In this paper we propose a frame of solving the SLAM problem of linking map covering, map building, localizing, path finding and obstacle avoiding in an automatic way. Some algorithms integrating grid and topology map are considered and this make the SLAM performance faster and more stable. The proposed scheme uses an occupancy grid map in representing the environment and then formulate topological information in path finding by A${\ast}$ algorithm. The mapping process is shown and the shortest path is decided on grid based map. Then topological information such as direction, distance is calculated on simulator program then transmitted to robot hardware devices. The localization process and the dynamic obstacle avoidance can be accomplished by topological information on grid map. While mapping and moving, pose of the robot is adjusted for correct localization by implementing additional pixel based image layer and tracking some features. A laser range finer and electronic compass systems are implemented on the mobile robot and DC geared motor wheels are individually controlled by the adaptive PD control method. Simulations and experimental results show its performance and efficiency of the proposed scheme are increased.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.965-971
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• 2015

This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.