• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1354-1357
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• 2015

In this paper, the designed fish robot is researched and developed for aquarium underwater robot. This paper is a study on how the outside technology merely to find the location of fish robots without specific sensor or internal devices for these fish robot. The model of the fish is designed to detect the position of the optical flow of the Robotic Fish in the Simulink through Matlab. This paper intends to recognize the shape of the tank via a video device such as a camera or camcorder using an image processing technique to identify the location of the robotic fish. Here, we are applied to the image comparing algorithm by using the average color weight algorithm method. In this, position coordinate system is used to find the position coordinates of the fish to identify the position of the Robotic fish. It was verified by the performance test of design robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.885-888
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• 2018

This paper researches a way of detecting fish robots moving in an aquarium. The fish robot was designed and developed for interactions with humans in aquariums. It was studied merely to detect a moving object in an aquarium because we need to find the positions of moving fish robots. The intention is to recognize the location of robotic fish using an image processing technique and a video camera. This method is used to obtain the velocity for each pixel in an image, and assumes a constant velocity in each video frame to obtain positions of fish robots by comparing sequential video frames. By using this positional data, we compute the distance between fish robots using a mathematical expression, and determine which fish robot is leading and which one is lagging. Then, the lead robot will wait for the lagging robot until it reaches the lead robot. The process runs continuously. This system is exhibited in the Busan Science Museum, satisfying a performance test of this algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.219-224
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• 2015

In this paper, the designed fish robots DOMI ver1.0 is researched and development for aquarium underwater robot. The presented fish robot consists of the head, 1'st stage body, 2nd stage body and tail, which is connected two point driving joints. The model of the robot fish is analysis to maximize the momentum of the robot fish and the body of the robot is designed through the analysis of the biological fish swimming. Also, Lighthill was applied to the kinematics analysis of robot fish swimming algorithms, we are applied to the approximate method of the streamer model that utilizes techniques mimic the biological fish. The swimming robot has two operating mode such as manual and autonomous operation modes. In manual mode the fish robot is operated to using the RF transceiver, and in autonomous mode the robot is controlled by microprocessor board that is consist PSD sensor for the object recognition and avoidance. In order to the submerged and emerged, the robot has the bladder device in a head portion. The robot gravity center weight is transferred to a one-axis sliding and it is possible to the submerged and emerged of DOMI robot by the breath unit. It was verified by the performance test of this design robot DOMI ver1.0. It was confirmed that excellent performance, such as driving force, durability and water resistance through the underwater field test.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1341-1344
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• 2015

In this paper, the designed fish robot is researched and developed for aquarium underwater robot. This paper is a study on how the outside technology merely to find the location of fish robots without specific sensor or internal devices. This model is designed to detect the position of the Robotic Fish in the Mat lab and Simulink. This intends to recognize the shape of the tank via a video device such as a camera or camcorder using an image processing technique to identify the location of the robotic fishes. Here, we are applied the two methods, one is Hom - Schunk Method and second one is newly proposed method that is the comparing image data algorithm. The Horn - Schunck Method is used to obtain the velocity for each pixel in the image and the comparing image data algorithm is proposed to obtain the position with comparing two video frames and assumes a constant velocity in each video frame.