• Title/Summary/Keyword: Aquarium robot system

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Robot Fish Tracking Control using an Optical Flow Object-detecting Algorithm

  • Shin, Kyoo Jae
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.6
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    • pp.375-382
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    • 2016
  • This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.

Realization of Fairy Tale - Robot Aquarium Display System with Visitor Interaction (관람객과 상호 교감하는 전래동화-로봇의 수중무대 연출시스템 구현)

  • Shin, Kyoo-Jae
    • Journal of IKEEE
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    • v.22 no.4
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    • pp.1180-1187
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    • 2018
  • This paper had implemented the underwater stage through interaction with fish robots and visitors in the background of traditional fairy tales using 3D floating hologram in an aquarium. The recognition of the object position of the spectator and the underwater robot were performed using the color recognition algorithm. Also, the position tracking algorithm was proposed to follow the object of the visitor and the original fairy tale. This experimental system consists of fish robot, camera, KIOSK for underwater robot control and beam project for underwater imaging. This experiment was carried out by the National Busan Science Museum, and it had satisfied the performance of the underwater stage.

Implementation of Fish Robot Tracking-Control Methods (물고기 로봇 추적 제어 구현)

  • Lee, Nam-Gu;Kim, Byeong-Jun;Shin, Kyoo-Jae
    • 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.

A study of Detecting Fish Robot Position Using The Define Average Color Weight Algorithm (평상 색상 구분 알고리즘을 이용한 물고기 로봇 위치 검출 연구)

  • Angani, Amaranth Varma;Lee, Ju Hyun;Shin, Kyoo Jae
    • 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.