• Journal of the Korean Society for Precision Engineering
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• v.28 no.11
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• pp.1265-1271
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• 2011

These days the number of aged and disabled people is increasing rapidly. But most of the disabled or the aged who have the ability to work, want to engage in economic activities and solve social restrictions as well as their bad financial conditions. This paper concerns about the tracking control of an electric wheelchair robot for welfare vehicle where the seat and electric wheelchair are separated and electric wheelchair robot must be autonomously controlled without the help of assistant. So the aged or the disabled people can drive welfare vehicle by himself by adopting this system. Therefore the concept of both an autonomous driving of electric wheelchair and path tracking robots is required in this system. Finally we suggested fuzzy controller in order to control the path tracking of electric wheelchair robot and compared the capability of the proposed controller with conventional PID controller.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.81-86
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• 2004

This paper describes self-localization of a mobile robot from the multiple candidates of landmarks in outdoor environment. Our robot uses omnidirectional vision system for efficient self-localization. This vision system acquires the visible information of all direction views. The robot uses feature of landmarks whose size is bigger than that of others in image such as building, sculptures, placard etc. Robot uses vertical edges and those merged regions as the feature. In our previous work, we found the problem that landmark matching is difficult when selected candidates of landmarks belonging to region of repeating the vertical edges in image. To overcome these problems, robot uses the merged region of vertical edges. If interval of vertical edges is short then robot bundles them regarding as the same region. Thus, these features are selected as candidates of landmarks. Therefore, the extracted merged region of vertical edge reduces the ambiguity of landmark matching. Robot compares with the candidates of landmark between previous and current image. Then, robot is able to find the same landmark between image sequences using the proposed feature and method. We achieved the efficient self-localization result using robust landmark matching method through the experiments implemented in our campus.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.2
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• pp.148-153
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• 2014

Submerged bodies such as autonomous underwater vehicles (AUV) or remotely operated vehicles (ROV) are widely used in various fields of exploring underseas. Those bodies keep ballasting and deballasting for stable navigation and operation. Identifying the internal volumetric spaces of the bodies is a primary step for such an operation. Unfortunately, most CAD models given to the engineer do not properly represent the compartments since each face of a compartment exists as an independent entity rather than as a face that belongs to the compartment. In this paper, an algorithm that automatically identify the faces as a group that forms a closed volumetric space, i.e., a compartment is presented. A submerged body is sliced into a number of cross sections. Each sliced section is analyzed to yield closed loops that are sections of the compartment. Then, the associated closed loops are gathered along the longitudinal direction to form a compartment. The algorithm presented is shown to provide a practical and reasonable solution that can readily be used in various applications.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.4
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• pp.343-352
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• 2016

A multi-rotor vehicle is an unmanned vehicle consisting of multiple rotors. A multi-rotor vehicle can be categorized as tri-, quad-, hexa-, and octo-rotor depending on the number of the rotors. Multi-rotor vehicles have many advantages due to their agile flight capabilities such as the ability for vertical take-off, landing and hovering. Thus, they can be widely used for various applications including surveillance and monitoring in urban areas. Since multi-rotors are subject to uncertain environments and disturbances, it is required to implement robust attitude stabilization and flight control techniques to compensate for this uncertainty. In this research, an advanced nonlinear control algorithm, i.e. sliding mode control, was implemented. Flight experiments were carried out using an onboard flight control computer and various real-time autonomous attitude adjustments. The feasibility and robustness for flying in uncertain environments were also verified through real-time tests based on disturbances to the multi-rotor vehicle.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.10
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• pp.52-60
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• 2010

It is generally important to get a precise position information for autonomous unmanned vehicle(AUV) to run safely. For getting the position of AUV, the GPS has been using to navigation in a vehicle. Though it is useful to finding a position, it is difficult to precisely control a trajectory of the AUV due to large measuring error which may reach over 10 meters. Therefore to apply AUV it needs to compensate for the error. This paper proposes a method to more precisely localize AUV using three low-cost differential global positioning systems (DGPS). The distance errors between each DGPS are minimized as using the least square method (LSM) and the Kalman filter to eliminate a Gaussian white noise. The selected DGPS is cheaper and easier to set up than the RTK-GPS. It is also more precise than the general GPS. The proposed method can compensate the relatively position error according to stationary and moving distance of the AUV. For evaluating the algorithm by simulation, the DGPS signal with the Gaussian white noise to any points is generated by the AR model and compared with the measurement signal. It is confirmed that the proposed method can effectively compensate the position error as comparing with the measurement signal. The compensated position signal can be used to localize and control the AUV in the road.

• Journal of Ocean Engineering and Technology
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• v.29 no.6
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• pp.488-498
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• 2015

This paper presents the dynamic model of an AUV called HW200 for underwater surveillance. The mathematical model of HW200 is briefly introduced, considering its shape. The maneuvering coefficients were initially estimated using empirical formulas and a database of vehicles with similar shapes. A motion simulator, based on Simulink of Mathworks, was developed to evaluate the mathematical model of the vehicle and to tune the maneuvering coefficients. The parameters were finely tuned by comparing the experimental results and simulated responses generated with the simulator by applying the same control inputs as the experiment. The velocity of HW200 in the tuning process was fixed at a constant forward speed of 1.83 m/s. Simulations with variable speed commands were conducted, and the results showed good consistency in the motion response, attitude, and velocity of the vehicle, which were similar to those of the experiment even under the speed variation. This paper also discusses the feasibility of its application to a model-based integrated navigation system (INS) using the auxiliary information on the velocities generated by the model.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.262-270
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• 2022

The emergence of new concept ships, such as autonomous ships, has drawn much attention on the manoeuvrability of ships because of the safe navigation and operation of ships. Although the manoeuvrability of KRISO Container Ship(KCS) has been frequently reported, there have been few documents of representative manoeuvre cases conducted in various methods by one institute. This paper presents the manoeuvrability of the ship in 1/42.0 model scale by 3 methods: free running model tests, horizontal planar motion mechanism tests, and computational fluid dynamics analysis. KRISO reports KCS manoeuvre data: 35° turning circle tests and 20/20(10/10) zigzag manoeuvring tests. In addition, a simple formula for integrating and comparing manoeuvre indices, Manoeuvrability Comparing Simple Index(MCSI), is proposed.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.248-255
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• 2023

In order to implement the autonomous navigation function, it is essential to track an object within a certain radius of the ship's route. This paper proposes the Multiple Probabilistic Data Association Filter (MPDAF), which can track multiple ships by extending Probabilistic Data Association Filter (PDAF), an existing single object tracking algorithm, using radar data obtained from real marine environments. The proposed MPDAF algorithm was developed to address the problem of tracking multiple objects in a complex environment where there can be significant uncertainty in the number and identification of objects to be tracked. Using real-world radar data provided by the German aerospace center (DLR), it has been verified that the proposed algorithm can track a large number of objects with a small position error.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.17-24
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• 2006

Though the final goal of mobile robot navigation is to be autonomous, operators' intelligent and skillful decisions are necessary when there are many scattered obstacles. There are several limitations even in the camera-based tele-operation of a mobile robot, which is very popular for the mobile robot navigation. For examples, shadowed and curved areas cannot be viewed using a narrow view-angle camera, especially in bad weather such as on snowy or rainy days. Therefore, it is necessary to have other sensory information for reliable tele-operations. In this paper, sixteen ultrasonic sensors are attached around a mobile robot in a ring pattern to measure the distances to obstacles. A collision vector is introduced in this paper as a new tool for obstacle avoidance, which is defined as a normal vector from an obstacle to the mobile robot. Based on this collision vector, a virtual reflection force is generated to avoid the obstacles and then the reflection force is transferred to an operator who is holding a joystick to control the mobile robot. Relying on the reflection force, the operator can control the mobile robot more smoothly and safely. For this bi-directional tele-operation, a master joystick system using a hall sensor was designed to resolve the existence of nonlinear sections, which are usual for a general joystick with two motors and potentiometers. Finally, the efficiency of a force reflection joystick is verified through the comparison of two vision-based tele-operation experiments, with and without force reflection.