• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2360-2362
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• 1998

This paper presents a new collison-free trajectory problem for SCARA robot manipulator. we use artificial potential field for collison detection and avoidance. The potential function is typically defined as the sum of attractive potential pulling the robot toward the goal configuration and a repulsive potential pushing the robot away from the obstacles. In here, end-effector of manipulator is represented as a particle in configuration space and moving obstacles is simply represented, too. we consider not fixed obstacle but moving obstacle in random. So, we propose new distance function of artificial potential field with moving obstacle for SCARA robot. At every sampling time, the artificial potential field is update and the force driving manipulator is derived from the gradient vector of artificial potential field. To real-time path planning, we apply very simple modeling to obstacle. Some simulation results show the effectiveness of the proposed approach.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.72-82
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• 2002

This paper presents the design technology of a Graphic Generator which drives the embedded aircraft display equipments such as HUD(Head-Up Display) and MFD (Multi-Function Display) those provide pilot with the most important mission information. The main issue of this design is how we can implement the real-time embedded graphic generator using a general purpose processor as a substitute for the obsolete the production of specific graphic processor in the military market. So we proposed two kinds of method that one is a software solution so called graphic kernel system, interpreting the display file, controlling the graphic system and pre-processing graphic primitives, the other is a hardware solution so called graphic engine, interpreting passed commands through the graphic kernel system, post-processing the looping calculation taking much of time as implemented by software. We have tested and verified the functionalities and the required performance of Graphic Generator.

• Journal of Mechanical Science and Technology
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• v.19 no.12
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• pp.2205-2212
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• 2005

In this paper, the cutting torque of a CNC machine tool during machining is monitored through the internet. To estimate the cutting torque precisely, the spindle driving system is divided into two parts: electrical induction motor part and mechanical part. A magnetized current is calculated from the measured three-phase stator currents and used for the total torque estimation generated by a spindle motor. Slip angular velocity is calculated from the magnetized current directly, which gets rid of the necessity of a spindle speed sensor. Since the frictional torque changes according to the cutting torque and the spindle rotational speed, an experiment is adopted to obtain the frictional torque as a function of the cutting torque and the spindle rotation speed. Then the cutting torque can be calculated by solving a $2^{nd}$ order difference equation at a given cutting condition. A graphical programming method is used to implement the torque monitoring system developed in this study to the computer and at the same time monitor the torque of the spindle motor in real time through the internet. The cutting torque of the CNC lathe is estimated well within an about $3\%$ error range in average in various cutting conditions.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.235-243
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• 2018

Conventional Real Time Kinematics (RTK) collect measurements in stationary state for several minutes to resolve the integer ambiguity in the carrier phase measurement or resolve the integer ambiguity on the move assuming low maneuvering movement. In this paper, an On The Move-RTK (OTM-RTK) technique that resolves the integer ambiguity on the move for fast and precise positioning of ground vehicles such as high maneuvering vehicles was proposed. The OTM-RTK estimates the precise amount of movement between epochs using the carrier phase measurements acquired on the move, and by using this, resolves the integer ambiguity within a short period of time by evaluating the integer ambiguity candidates for each epoch. This study analyzed the integer ambiguity resolution performance using field driving experiment data in order to verify the performance of the proposed method. The results of the experiment showed that the precise trajectory including the initial position bias can be obtained prior to resolving the integer ambiguity, and after resolving the integer ambiguity on the move, it was possible to obtain the bias-corrected precise position solution. It was confirmed that the integer ambiguity can be resolved by collecting measurements of about 10 epochs from the moving vehicle using a dual frequency receiver.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.112-121
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• 2021

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

• Smart Media Journal
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• v.12 no.11
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• pp.57-66
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• 2023

In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.125-138
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• 2011

The highway visibility reduction caused by fog is one of the major elements of traffic accidents. Though the fog warning systems can lead drivers into safe driving by letting them aware dangerous situations in advance, the optical sensors, such as fog sensor, has been extremely costly. Through recent studies, it is delivered that visibility measurements have become obtainable with relatively cheap cameras and their functionality is as similar as a driver' visual sense. Those measurements however require additional signs or ROI, so it is still costly and unable to utilize the conventional images from the existing systems. This study proposes a new method to detect the visibility in real time based on the conventional images from the existing CCTV cameras. The proposed method builds a road model and extracts and applies vehicle movements and visible lines - those highlight easy and quick visibility measurements. The proposed method has advantages of both (1) having possible day and night visibility measurements similar to drivers' visual sense and (2) being easily applied to the existing CCTV system without additional devices. This paper presents field experiments using images acquired from the Central Inland Expressway and discusses future research directions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.673-679
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• 2012

Vehicle rollover is a serious kind of accident, particularly for sport utility vehicles, and its occurrence can be minimized by utilizing active rollover prevention systems. The performance of these protection systems is very sensitive to vehicle inertial parameters such as the vehicle's mass and center of mass. These parameters vary with the number of passengers and in different load situations. In this paper, a unified method for vehicle mass estimation is proposed that takes into account the available driving conditions. Three estimation algorithms are developed based on longitudinal, lateral, and vertical vehicle motion, respectively. Then, the three algorithms are combined to extract information on the vehicle's mass during arbitrary vehicle maneuvering. The performance of the proposed vehicle mass estimation method is demonstrated through real-time experiments.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.408-416
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• 2017

This paper proposes a real-time side-rear vehicle detection algorithm that detects vehicles quickly and accurately in blind spot areas when driving. The proposed algorithm uses a cascade classifier created by AdaBoost Learning using the MCT (modified census transformation) feature vector. Using this classifier, the smaller the detection window, the faster the processing speed of the MCT classifier, and the larger the detection window, the greater the accuracy of the MCT classifier. By considering these characteristics, the proposed algorithm uses two classifiers with different detection window sizes. The first classifier quickly generates candidates with a small detection window. The second classifier accurately verifies the generated candidates with a large detection window. Furthermore, the vehicle classifier and the wheel classifier are simultaneously used to effectively detect a vehicle entering the blind spot area, along with an adjacent vehicle in the blind spot area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.590-598
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• 2016

It comes into the spotlight as the new Blue Ocean in which the connected car industry in which the car and mobile communication technology is convergence. All sorts of infortainments services connecting with the portable electronic device(Smart phone, tablet PC, and MP3 player) and car are rapidly grown. The Connected car emphasizes the vehicle connectivity with the concept that the car has communication with the around on a real time basis and it provides the safety and expedience to the operator and using the thing of Internet (IoT) in the car and supports the application, presently, the entertainment service including the real-time Navigation, parking assistant function, not only the remote vehicle control and management service but also Email, multimedia streaming service, SNS and with the platform. Intelligent vehicle network is studied as the kind according to MANET(Mobile Ad Hoc Network) for the safety operation of the cars of the road and improving the efficiency of the driving.