• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.99-108
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• 2014

Recently, the interest in autonomous vehicle which is an aggregate of the automotive control technology is increasing. In particular, researches on the self-localization technology that is directly connected with stable driving of autonomous vehicle have been performed. Various dead reckoning technologies which are solutions for resolving the limitation of GPS have been introduced. However, the conventional dead reckoning technologies have two disadvantages to apply on the autonomous vehicle. First one is that the expensive sensors must be equipped additionally. The other one is that the accuracy of self-localization decreases caused by wheel slip when the vehicle's motion changed rapidly. Based on this background, in this paper, the wheel speed sensor which is equipped on most of vehicles was used and the dead reckoning algorithm considering wheel slip ratio was developed for autonomous vehicle. Finally, in order to evaluate the performance of developed algorithm, the various simulation were conducted and the results were compared with the conventional algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.674-682
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• 2003

Ship autonomous navigation is designated as what computerizes mental faculties possessed of navigation experts, which are building navigation plans, grasping the situation, forecasting the fluctuation, and coping with the situation. An autonomous navigation system, which consists of several subsystems such as navigation system, a collision avoidance system, several data fusion systems, and a motion control system, is based on an intelligent control architecture for the sake of integrating the systems. The motion control system, which is one of the most essential system in autonomous navigation system, controls its propulsion and steering gears to move the ship satisfying its hydrodynamic characteristics. This paper is the study on the ship movement control system and its implementation which are totally developed and run on virtual-world system. Receiving the high-level control values such as a waypoint presented from the collision avoidance system, the motion control system generates them to low-level control values for propulsion and steering devices. In the paper, we develop a ship motion controller using Oldenburger's theory based on mathematical fundamentals, and simulate it with various scenarios in order to verify its performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.323-328
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• 2011

In real system application, the 3-D obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: the sonar offers the range/bearing information of obstacles in a local detection area, it requires the system that has reduced acoustic noise and power consumption in terms of the autonomous underwater vehicle (AUV), it has the UFV operation constraints such as maximum pitch and depth, and it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent 3-D obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the 3-D obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.242-263
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• 2021

This paper presents a method to implement a low-cost driving simulator for developing autonomous driving algorithms. This is implemented by using GTA V, a physical engine-based commercial game software, containing a function to emulate output and data of various sensors for autonomous driving. For this, NF of Script Hook V is incorporated to acquire GT data by accessing internal data of the software engine, and then, various sensor data for autonomous driving are generated. We present an overall function of the developed driving simulator and perform a verification of individual functions. We explain the process of acquiring GT data via direct access to the internal memory of the game engine to build up an autonomous driving algorithm development environment. And, finally, an example applicable to artificial neural network training and performance evaluation by processing the emulated sensor output is included.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.779-784
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• 2008

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.231-239
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• 2010

For indoor mobile robots, the performance of autonomous navigation is affected by a variety of factors. In this paper, we focus on the characteristics of indoor absolute positioning systems. Two commercially available sensor systems are experimentally tested under various conditions. Mobile robot navigation experiments were carried out, and the results show that resultant performance of navigation is highly dependent upon the characteristics of positioning systems. The limitations and characteristics of positioning systems are analyzed from both quantitative and qualitative point of view. On the basis of the analysis, the relationship between the positioning system characteristics and the controller design are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.81-86
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• 2015

GPS position errors were corrected for guidance of autonomous vehicles. From the vision, we can obtain the lateral distance from the center of lane and the angle difference between the left and right detected line. By using a controller which makes these two measurements zero, a lane following system can be easily implemented. However, the problem is that if there's no lane, such as crossroad, the guidance system of autonomous vehicle does not work. In addition, Line detection has problems working on curved areas. In this case, the lateral distance measurement has an error because of a modeling mismatch. For this reason, we propose GPS error correction filter based on curve-modeled lane detection and evaluated the performance applying it to an autonomous vehicle at the test site.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.674-684
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• 2011

More and more elderly and disabled people are using electric scooters instead of electric wheelchairs because of higher mobility. However, people with high levels of impairment or the elderly still have difficulties in driving the electric scooters safely. Semi-autonomous electric scooter system is one of the solutions for the safety: Either manual driving or autonomous driving can be used selectively. In this paper, we implement a semi-autonomous electric scooter system with functions of localization and path following. In order to recognize the pose of electric scooter in outdoor environments, we design an outdoor localization system based on the extended Kalman filter using DGPS (Differential Global Positioning System) and wheel encoders. We added an accelerometer to make the localization system adaptable to road condition. Also we propose a path following algorithm using two arcs with current pose of the electric scooter and a given path in the map. Simulation results are described to show that the proposed algorithms provide the ability to drive an electric scooter semi-autonomously. Finally, we conduct outdoor experiments to reveal the practicality of the proposed system.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.29-34
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• 2013

This study presents the remote control of a mobile robot using iPhone based on ad hoc communication. Two control interfaces are proposed to control a mobile robot using iPhone : Remote control by a user and autonomous control. To evaluate the effectiveness of algorithms for trajectory following, a simulator are developed where a virtual robot follows a referenced trajectory in a monitor by iPhone interface. In the proposed simulator, some algorithms are tested how they work well or not for trajectory following of a mobile robot. Comparative results by remote user control and autonomous control are shown. Results of an experiment show that the proposed simulator can be effectively used for testing the effectiveness of autonomous tracking algorithms.