• International Journal of Automotive Technology
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• v.6 no.5
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• pp.545-554
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• 2005

Passive velocity field control (PVFC) was previously developed for fully mechanical systems, in which the motion task was specified by behaviors in terms of a velocity field and the closed-loop was passive with respect to the supply rate given by the environment input. However, the PVFC was only applied to a single manipulator. The proposed control law was derived geometrically and the geometric and robustness properties of the closed-loop system were also analyzed. In this paper, we propose a virtual passivity-based algorithm to apply decentralized control to multiple 3­wheeled mobile robotic systems whose subsystems are under nonholonomic constraints and convey a common rigid object in a horizontal plain. Moreover, it is shown that multiple robot systems ensure stability and the velocities of augmented systems converge to a scaled multiple of each desired velocity field for cooperative mobile robot systems. Finally, the application of proposed virtual passivity-based decentralized algorithm via system augmentation is applied to trace a circle and the simulation results is presented in order to show effectiveness for the decentralized control algorithm proposed in this research.

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.269-276
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• 2015

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we discussed the state-of-the-art of the domestic and international use of UAV in agricultural sector as well as assessed its utilization and applicability for agricultural environment in Korea. Association of robotic, computer vision and geomatic technologies have established a new paradigm of low-altitude aerial remote sensing that has now been receiving attention from researchers all over the world. In a field study, it has been found that use of UAV imagery in an agricultural subsidy program can reduce the farmers' complain and provide objective evidence. UAV high resolution photography can also be helpful in monitoring the disposal zone for animal carcasses. Due to its expeditiousness and accuracy, UAV imagery can be a very useful tool to evaluate the damage in case of an agricultural disaster for both parties insurance companies and the farmers. Also high spatial and temporal resolution in UAV system can increase the prediction accuracy which in turn help to maintain the agricultural supply and demand chain.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.198-203
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• 2004

This paper describes a real-time control architecture for DUSAUV (Dual Use Semi-Autonomous Underwater Vehicle), which has been developed at Korea Research Institute of Ships & Ocean Engineering (KRISO), KORDI, for being a test-bed oj development of technologies for underwater navigation and manipulator operation. DUSAUV has three built-in computers, seven thrusters for 6 degree of freedom motion control, one 4-function electric manipulator, one pan/tilt unit for camera, one ballasting motor, built-in power source, and various sensors such as IMU, DVL, sonar, and so on. A supervisor control system for GUI and manipulator operation is mounted on the surface vessel and communicates with vehicle through a fiber optic link. Furthermore, QNX, one of real-time operating system, is ported on the built-in control and navigation computers of vehicle for real-time control purpose, while MicroSoft OS product is ported on the supervisor system for GUI programming convenience. A hierarchical control architecture which consist of three layers (application layer, real-time layer, and physical layer) has been developed for efficient control system of above complex underwater robotic system. The experimental results with implementation of the layered control architecture for various motion control of DUSAUV in a basin of KRISO is also provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.26-32
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• 2016

An autonomous car(driverless car, self-driving car, robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars can detect surroundings using a variety of techniques such as radar, lidar, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination. An issue tree, also called a logic tree, is a graphical breakdown of a question that dissects it into its different components vertically and that progresses into details as it reads to the right.Issue trees are useful in problem solving to identify the root causes of a problem as well as to identify its potential solutions. They also provide a reference point to see how each piece fits into the whole picture of a problem. Using Issue-Tree menthods, transportation safety policies were developed with autonompus vehicle in mind.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.164-170
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• 2013

Quadrotor UAV (Unmanned Aerial Vehicle) is a flying robotic platform which has drawn lots of attention in the recent years. The attraction comes from the fact that it is able to perform agile VTOL (Vertical Take-Off Landing) and hovering functions. In addition, the efficient modular structure composed of four electric rotors makes its design easier compared to other single-rotor type helicopters. In many cases, a quadrotor often utilizes vision systems in order to obtain altitude control and navigation solution in hostile environments where GPS receivers are not working or deniable. For carrying out their successful missions, it is essential for flight control systems to have fast and stable control responses of heading angle outputs. This paper presents a Fuzzy Logic based lateral PI controller to stabilize and control the quadrotor vehicle equipped with vision systems. The advantage of using the fuzzy based PI controller lies in the fact that it could acquire a desired output response of a heading angle even in presence of disturbances and uncertainties. The performance comparison of the newly proposed Fuzzy-PI controller and the conventional PI controller was carried out with various simulation results.

• Journal of Ecology and Environment
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• v.41 no.3
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• pp.72-77
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• 2017

The world of technology is pleasantly evolving to a stage where small robotic aid may be used to ease the work of researchers, and to one day bring more accurate results than the current human abilities allow. In the research field of species monitoring in biology, unmanned aerial vehicles (UAVs) have begun to play an important role in how research is approached, analyzed, and then applied for further investigation, particularly by focusing on a single species. This paper uses data that has been collected from June to October 2015, to demonstrate how the innovative idea of using UAVs to monitor a particular species will bring a positive development in conservation research, and what it was able to achieve in this research field so far. More precisely, we examine the potential of UAVs to take center stage in future research, as well as their current accuracy. This paper describes the use of the commercially available Phantom 2 Vision+ for the detection, assessment, and monitoring of the butterfly species Libythea celtis, demonstrating how it can help the monitoring of butterflies and how it could be developed for even more adventurous and detailed research in the future.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.91-96
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• 2001

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamics, and a sliding mode control is introduced to attenuate the effects of the neural network's reconstruction errors and the disturbances of AUV's dynamics. The presented controller is consist of three parallel schemes; linear feedback control, sliding mode control and neural network. Lyapunov theory is used to guarantee the asymptotic convergence of trajectory tracking errors and the neural network's weights errors. Numerical simulations for motion control of an AUV are performed to illustrate to effectiveness of the proposed techniques.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.194-200
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• 2016

Recently, UUVs (unmanned underwater vehicles) have increasingly been applied in various science and engineering applications. In-water inspection, which used to be performed by human divers, is a potential application for UUVs. In particular, the operational safety and performance of in-water inspection missions can be greatly improved by using an underwater robotic vehicle. The capabilities of hovering maneuvers and automatic image mosaicking are essential for autonomous underwater visual inspection. This paper presents the development of a hover-capable autonomous underwater vehicle system for autonomous in-water inspection, which includes both a hardware platform and operational software algorithms. Some results from an experiment in a model basin are presented to demonstrate the feasibility of the developed system and algorithms.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.8-15
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• 2002

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.402-410
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• 2017

Acoustic based localization is essential to operate autonomous robotic systems in underwater environment where the use of sensorial data is limited. This paper proposes a localization method using artificial underwater acoustic sources. The proposed method acquires directional angles of acoustic sources using time difference of arrivals of two hydrophones. For this purpose, a probabilistic approach is used for accurate estimation of the time delay. Then, Gaussian sum filter based SLAM technique is used to localize both acoustic sources and underwater vehicle. It is performed by using bearing of acoustic sources as measurement and inertial sensors as prediction model. The proposed method can handle directional ambiguity of time difference based source localization by generating Gaussian models corresponding to possible locations of both front and back sides. Through these processes, the proposed method can provide reliable localization method for underwater vehicles without any prior information of source locations. The performance of the proposed method is verified by experimental results conducted in a real sea environment.