• 제어로봇시스템학회논문지
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• 제10권5호
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• pp.442-449
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• 2004

As underwater robotic vehicles (URVs) become attractive for more sophisticated underwater tasks, the demand of high performance in terms of accuracy and dexterity has been increased. An autonomous underwater robotic vehicle, ODIN (Omni-Directional Intelligent Navigator) was designed and built at the Autonomous Systems Laboratory of the University of Hawaii in 1991. Since 1991, various studies were conducted on ODIN and have contributed to the advancement in underwater robotics. Its refurbished model ODIN II was based on VxWorks in VMEbus. Recently, ODIN was born again as a PC based system, ODIN III with unique features such as new vehicle system software architecture with an objective-oriented concept, a graphical user interface, and an independent and modular structure using a Dynamic Linking Library (DLL) based on the Windows operating system. ODIN III software architecture offers an ideal environment where various studies for advanced URV technology can be conducted. This paper describes software architecture of ODIN III and presents initial experimental results of fine motion control on ODIN III.

• 한국해양공학회지
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• 제33권6호
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• pp.510-517
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• 2019

Efficient path planning is essential for unmanned surface vehicle (USV) navigation. The A^* algorithm is an effective algorithm for identifying a safe path with optimal distance cost. In this study, a modified version of the A^* algorithm is applied for planning the path of a USV in a static and dynamic obstacle environment. The current study adopts the A^* approach while maintaining a safe distance between the USV and obstacles. Two important parameters-path length and computational time-are considered at various start times. The results demonstrate that the modified approach is effective for obstacle avoidance by a USV that is compliant with the International Regulations for Preventing Collision at Sea (COLREGs).

• 한국지능시스템학회논문지
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• 제21권4호
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• pp.430-435
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• 2011

본 논문에서는 상대위치인식과 자계기반 안내를 결합한 무인주행 차량의 주행기법을 제안한다. 자계기반 주행은 이동하는 경로에 자계가 항상 계측되면 안정적인 자율주행이 가능하다. 하지만 외부요인으로 인해 자계가 검출되지 않으면 예측 불가능한 상황이 발생하는 단점이 있다. 따라서 상대위치인식을 이용한 무인주행을 통해 자계가 검출되지 않는 구간을 극복하는 방법을 제안하였다. 제안한 방법의 유용함을 검증하기 위하여 차량을 개발하고 자계기반 주행 실험하였다. 또한 자계가 없는 구간에서의 상대항법을 이용한 무인주행 실험을 실시하고 결과를 분석하여 문제점 극복의 가능성을 확인하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.320-325
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• 1998

Underwater robotic vehicles (URVs) have been an important tool for various underwater tasks because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system becomes one of the most critical subsytems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. In this paper a new type of fuzzy model-based controller based on Takagi-Sugeno-Kang fuzzy model is designed and applied to the control of of an underwater robotic vehicle. The proposed fuzzy controller : 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule ; 2) can guarantee the stability of the closed-loop fuzzy system ; 3) is relatively easy to implement. Its good performance as well as its robustness to the change of parameters have been shown and compared with the re ults of conventional linear controller by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.43.4-43
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• 2002

$\textbullet$ Introdution $\textbullet$ Robotic Suspension $\textbullet$ Vehicle Dynamics $\textbullet$ Result $\textbullet$ Conclusion

• 한국자동차공학회논문집
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• 제13권4호
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• pp.19-25
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• 2005

This paper presents a lateral control system for the autonomous navigation vehicle that was developed and tested by Robotics Centre of Ecole des Mines do Paris in France. A robust lane detection algorithm was developed for detecting different types of lane marker in the images taken by a CCD camera mounted on the vehicle. $^{RT}Maps$ that is a software framework far developing vision and data fusion applications, especially in a car was used for implementing lane detection and lateral control. The lateral control has been tested on the urban road in Paris and the demonstration has been shown to the public during IEEE Intelligent Vehicle Symposium 2002. Over 100 people experienced the automatic lateral control. The demo vehicle could run at a speed of 130km1h in the straight road and 50km/h in high curvature road stably.

• 국제초고층학회논문집
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• 제11권2호
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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.

• 수산해양기술연구
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• 제33권4호
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• pp.290-297
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• 1997

Underwater robotic vehicles(URVs) are used for various work assignments such as pipe-lining, inspection, data collection, drill support, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc. As the use of such vehicles increases the development of vehicles having greater autonomy becomes highly desirable. The vehicle control system is one of the most critic vehicle subsystems to increase autonomy of the vehicle. The vehicle dynamics is nonlinear and time-varying. Hydrodynamic coefficients are often difficult to accurately estimate. It was also observed by experiments that the effect of electrically powered thruster dynamics on the vehicle become significant at low speed or stationkeeping. The conventional linear controller with fixed gains based on the simplified vehicle dynamics, such as PID, may not be able to handle these properties and result in poor performance. Therefore, it is desirable to have a control system with the capability of learning and adapting to the changes in the vehicle dynamics and operating parameters and providing desired performance. This paper presents an adaptive and learning control system which estimates a new set of parameters defined as combinations of unknown bounded constants of system parameter matrices, rather than system parameters. The control system is described with the proof of stability and the effect of unmodeled thruster dynamics on a single thruster vehicle system is also investigated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• 한국자동차공학회논문집
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• 제4권3호
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• pp.73-82
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• 1996

Vehicle movement detection by high order correlation analysis of optical sensor array signals is introduced. The optical sensors observe the road which is assumed to be a non-uniform speckle-like texture. The measurement system is applicable to general robotic movement detection because : 1) It employs a non-contact measurement method, 2) The system can be made very compact, and 3) It enables approximation of the movement trace with a sequence of arcs instead of the conventional connection of simple line segments. In this work, we have looked into estimation of running trace of an autonomous vehicle by observing the ground pattern.