• 로봇학회논문지
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• 제7권4호
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• pp.284-291
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• 2012

Recently, development of underwater robot has actively been in progress in the world as ROV(Remotely Operator Vehicle) and AUV(Autonomous Unmmanded Vehicle) style. But KIOST(Korea Institute of Ocean Science and Technology), beginning in 2010, launched the R&D project to develop the robot, dubbed CRABSTER(Crab + (Lob)ster) in a bid to enhance the safety and efficiency of resource exploration. CRABSTER has been designed to be able to walk and swim with its own legs without screws. Among many research subjects regarding CRABSTER, optimal swimming patterns are handled in this paper. In previous studies, drag forces during one period with different values for angle of each joint were derived. However kinematics of real-robot and fluid-dynamics are not considered. We conducted simulations with an optimization algorithm for swimming by considering simplified fluid dynamics in this paper. Drag-coefficients applied to the simulation were approximated values calculated by CFD(Computational Fluid Dynamics : Tecplot 360, ANSYS). In addition, optimized swimming patterns were applied to a real robot. The experiments with the real robot were conducted in circumstances in the water. As a result, when the experiments were carried out in the water, a regular pattern of drag force output came out depending on the movement of the robot. We confirmed the fact that the drag forces from the simulation and the experiment has a high similarity.

• 한국해양공학회지
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• 제36권1호
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• pp.41-49
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• 2022

With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

• IEIE Transactions on Smart Processing and Computing
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• 제4권4호
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• pp.216-223
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• 2015

The autonomous underwater vehicle (AUV) is being widely researched in order to achieve superior performance when working in hazardous environments. This research focuses on using image processing techniques to estimate the AUV's egomotion and the changes in orientation, based on image frames from different time frames captured from a single high-definition web camera attached to the bottom of the AUV. A visual odometry application is integrated with other sensors. An internal measurement unit (IMU) sensor is used to determine a correct set of answers corresponding to a homography motion equation. A pressure sensor is used to resolve image scale ambiguity. Uncertainty estimation is computed to correct drift that occurs in the system by using a Jacobian method, singular value decomposition, and backward and forward error propagation.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• 로봇학회논문지
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• 제7권4호
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• pp.259-266
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• 2012

In these days, researches about underwater robots have been actively in progress for the purposes of ocean detection and resource exploration. Unlike general underwater robots such as ROV(Remotely Operated Vehicle) and AUV(Autonomous Underwater Vehicle) which have propellers, an articulated underwater robot which is called Crabster has been being developed in KORDI(Korea Ocean Research & Development Institute) with many cooperation organizations since 2010. The robot is expected to be able to walk and swim under the sea with its legs. Among many researching fields of this project, we are focusing on a swimming section. In order to find effective swimming locomotion for the robot, we approached this subject in terms of Biomimetics. As a model of optimized swimming organism in nature, diving beetles were chosen. In the paper, swimming motions of diving beetles were analyzed in viewpoint of robotics for applying them into the swimming motion of the robot. After modeling the kinematics of diving beetle through robotics engineering technique, we obtained swimming patterns of the one of living diving beetles, and then compared them with calculated optimal swimming patterns of a robot leg. As the first trial to compare the locomotion data of legs of the diving beetle with a robot leg, we have sorted two representative swimming patterns such as forwarding and turning. Experimental environment has been set up to get the motion data of diving beetles. The experimental equipment consists of a transparent aquarium and a high speed camera. Various swimming motions of diving beetles were recorded with the camera. After classifying swimming patterns of the diving beetle, we can get angular data of each joint on hind legs by image processing software, Image J. The data were applied to an optimized algorithm for swimming of a robot leg which was designed by robotics engineering technique. Through this procedure, simulated results which show trajectories of a robot leg were compared with trajectories of a leg of a diving beetle in desired directions. As a result, we confirmed considerable similarity in the result of trajectory and joint angles comparison.

• 정보처리학회논문지A
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• 제16A권4호
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• pp.255-262
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• 2009

유비쿼터스 센서 네트워크(USN)에 기반한 엔터테인먼트용 자율 돌고래 로봇의 구현에 관하여 소개한다. 일반적으로 수중에서 동작하는 생체모방 로봇에 유비쿼터스 센서 네트워크와 GPS를 적용하는 것은 불가능한 일이다. 본 논문에서 제안된 엔터테인먼트용 돌고래 로봇은 수중이 아닌 수면에서 동작하므로, 사용자와의 상호작용을 중요시하며 제안된 수중 로봇의 네비게이션은 GPS정보와 배치된 USN 모트로부터 얻어진 미세한 위치 정보로부터 수행된다. 본 논문에서는 제안된 돌고래 로봇의 기계적인 구조, 센서와 엑추에이터, 마이크로컨트롤러 보드와 수영 방법, 사용자와의 상호작용의 특징을 기술한다. 엔터테인먼트 돌고래 로봇은 유저에 의한 접촉 센서의 감지 신호를 입력받아 입을 움직이거나, 꼬리를 치고, 물을 뿜어내는 등의 전형적인 응답을 보인다. 로봇의 자율성을 위하여 경로 설정, 장애물 감지 및 회피 등과 같은 로봇의 움직임뿐 아니라 인간과 로봇의 상호작용에 관련된 기능들을 마이크로컨트롤러가 제어한다. 돌고래 로봇의 위치 정보는 배치된 USN 모트의 알려진 위치 정보로부터 주기적으로 교정된다.

• 수산해양기술연구
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• 제39권1호
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• pp.77-83
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• 2003

Autonomous mobile robots based on the Web have been already used in public places such as museums. There are many kinds of problems to be solved because of the limitation of Web and the dynamically changing environment. We present a methodology for intelligent mobile robot that demonstrates a certain degree of autonomy in navigation applications. In this paper, we focus on a mobile robot navigator equipped with neuro-fuzzy controller which perceives the environment, make decisions, and take actions. The neuro-fuzzy controller equipped with collision avoidance behavior and target trace behavior enables the mobile robot to navigate in dynamic environment from the start location to goal location. Most telerobotics system workable on the Web have used standard Internet techniques such as HTTP, CGI and Scripting languages. However, for mobile robot navigations, these tools have significant limitations. In our study, C# and ASP.NET are used for both the client and the server side programs because of their interactivity and quick responsibility. Two kinds of simulations are performed to verify our proposed method. Our approach is verified through computer simulations of collision avoidance and target trace.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권5호
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• pp.219-224
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• 2015

본 논문의 수중로봇 도미(Domi) ver1.0는 관상어용 물고기 로봇 개발을 목표로 연구 개발되었다. 물고기 로봇은 머리, 1단, 2단 몸체와 꼬리 부분과 2개의 구동 관절로 구성되어있다. 물고기 로봇의 추력에 적합한 구동부 선정을 위하여 물고기 로봇 모델링과 유영 해석을 통하여 관절 구동부가 설계되었다. 또한 물고기 로봇의 유영알고리즘은 Lighthill 운동학 해석을 기초로 생체 모방의 유영 근사화 방법을 적용하였다. 설계된 물고기는 수동유영 및 자율운영모드로 동작된다. 수동유영모드는 RF 송수신기를 이용하여 운용되며, 자율유영모드는 머리 부분에 부착된 PSD센서, 마이컴 제어부, 서보 구동장치에 의하여 구현된다. 본 설계된 물고기 로봇 도미 ver1.0은 수중 현장시험 평가를 통하여 추력, 내구성, 방수성 등의 성능이 우수함을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권2호
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• pp.91-99
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• 2013

An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

• 대한기계학회논문집A
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• 제33권10호
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• pp.1029-1037
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• 2009

Recently, the technologies of mobile robots have been growing rapidly in the fields such as cleaning robot, explosive ordnance disposal robot, patrol robot, etc. However, the researches about the autonomous underwater robots have not been done so much, and they still remain at the low level of technology. This paper describes a model of 3-joint (4 links) fish robot type. Then we calculate the dynamic motion equation of this fish robot and use Singular Value Decomposition (SVD) method to reduce the divergence of fish robot's motion when it operates in the underwater environment. And also, we analysis response characteristic of fish robot according to the parameters of input torque function and compare characteristic of fish robot with 3 joint and fish robot with 2 joint. Next, fish robot's maximum velocity is optimized by using the combination of Hill Climbing Algorithm (HCA) and Genetic Algorithm (GA). HCA is used to generate the good initial population for GA and then use GA is used to find the optimal parameters set that give maximum propulsion power in order to make fish robot swim at the fastest velocity.