• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.153-159
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• 2016

In this paper, a mechanism of an omni-directional personal mobility which can drive diagonally is proposed. Mobility is a prerequisite involved in basic human life and activities. Personal mobility vehicle is a new mobility method which overcome the limits of automobiles. However, personal mobilities with four wheeled structure still have limitations. The proposed personal mobility vehicle can overcome the limitations of mobility because its rear wheels can be steered omni-directionally. In addition, the handicapped can drive it through a narrow road such as an alleyway or corridor and avoid obstacles on the traveling route. The proposed mechanism of personal mobility and the steering performance are tested by experiments, and the feasibility of diagonal driving is verified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.521-526
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• 2016

This paper suggests a new design that makes use of rotary inertia that can allow autonomous movement of an autonomous colonoscope robot in the colon of a patient as a locomotive mechanism. As commercial colonoscopy causes a lengthy time of pain and discomfort to the patients when colonoscopy patients are reluctant to receive surgery, there is a tendency to avoid the test in the early diagnosis of colorectal cancer. To solve this problem, research has been conducted on the next generation of robotic colonoscopes that can reduce the discomfort and pain by moving autonomously within the colon of the patients. In the driving mechanism utilizing the rotational inertia, a flywheel is driven by a motor to store energy and produce rotational inertia. By the energy stored and released by the flywheel, the stick phenomenon that occurs when the robot is running in the intestine can be overcome effectively. To do this, a controller that can control the velocity of the flywheel and is robust to high frequency noise was designed and implemented. The driving mechanism using the rotational inertia presented here showed that the structure is also effective and the experiment can be run easily compared to another mechanism.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.4
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• pp.187-194
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• 2015

In this paper, we present an effective visual odometry estimation system to track the real-time pose of a camera moving in 3D space. In order to meet the real-time requirement as well as to make full use of rich information from color and depth images, our system adopts a feature-based sparse odometry estimation method. After matching features extracted from across image frames, it repeats both the additional inlier set refinement and the motion refinement to get more accurate estimate of camera odometry. Moreover, even when the remaining inlier set is not sufficient, our system computes the final odometry estimate in proportion to the size of the inlier set, which improves the tracking success rate greatly. Through experiments with TUM benchmark datasets and implementation of the 3D scene reconstruction application, we confirmed the high performance of the proposed visual odometry estimation method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.142-151
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• 2018

In the era of the 4th Industrial Revolution, research and development on autonomous vehicles have been actively conducted all over the world. Under these international trends, the Ministry of Land, Infrastructure and Transport is actively promoting the development of autonomous vehicles aiming at commercialization of autonomous vehicles at level 3 or higher by 2020. In the level 3 autonomous vehicle, it is essential to transfer control between the driver and the vehicle according to driving situations. Prior to the full-fledged autonomous vehicle age, this study developed a representative scenario for the safety evaluation on take-over on expressways. To accomplish this, we developed a highway driving scenario first, and then developed six control transition scenarios based on 2014 highway traffic accident data and take-over data. The variables to be considered in the developed scenarios are divided into drivers, vehicles, and environmental factors. A total of 36 variables are selected.

• Journal of Korea Game Society
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• v.15 no.4
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• pp.169-178
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• 2015

Providing various levels of difficulty of game play is one of important considerations in game development. In this paper, we propose a method for obtaining the challenges that will be placed on the track of an one-player car driving game. Herein challenges denote obstacles on the track, and the level of difficulty is represented by an estimated time needed for driving one lap of the track. In the proposed method, the problem for finding challenge placement is modeled as an IP(Integer Programming) one, and then LP relaxation and Simultaneous Annealing are employed to find a solution. To the experiment with the proposed method, we can obtain challenge placements to approximately meet given target driving times. Also, after practically driving on the track where those obtained challenges are being placed, it is seen that the average driving times approximate the target driving times of those challenge placements. Our method can allow game play with various levels of difficulty so that the users' interest and the level of immerse are expected to be raised.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.19-33
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• 2019

There have been enormous efforts to develop an innovative public transport bus service for enhancing its operational efficiency based on Automated Vehicle(AV). However, since the vehicle operating environment in the public transport system varies with the purpose and method of mobility service, it is necessary to preferentially evaluate the current roadworthiness for an effective way to introduce the AV. Therefore, this study classified and redefined AV-based mobility service based on literature reviews. This research conducted the roadworthiness test for checking the feasibilities of the AV-based mobility services. Furthermore, we suggested some deployment strategies of the AV-based mobility service considering the Level-Of-Service (LOS) of road infrastructure based on the results of roadworthiness tests. The proposed direction would have a great potential to introduce the AV-based public transport system in the near future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.223-230
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• 2021

Currently, self-driving vehicles are on the verge of commercialization after testing. However, even though autonomous vehicles have not been fully commercialized, 81 accidents have occurred, and the driving method of vehicles to avoid accidents relies heavily on LiDAR. In order for the currently commercialized 3-level autonomous vehicle to develop into a 4-level autonomous vehicle, more information must be collected than previously collected information. Therefore, this paper proposes a Driving Situation Judgment System (DSJS) that accurately calculates the crisis situation the vehicle is in by useing the roughness of the road and the state of the passengers of surrounding vehicles including road information and weather information collected from existing autonomous vehicles. As a result of DSJS's PDM experiment, PDM was able to classify passengers 15.52% more accurately on average than the existing vehicle's passenger recognition system. This study can be a basic research to achieve the 4th level autonomous vehicle by collecting more various types than the data collected by the existing 3rd level autonomous vehicle.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.12
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• pp.587-594
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• 2016

Autonomous A.I. vehicles are seemingly soon ready for our life. One of the critical problems with autonomous vehicles is how one could assign responsibility for accidents to them. We can envisage that autonomous vehicles may confront an ethical dilemma. Then a question arises of how we are able to assign legal responsibility to autonomous vehicles. In this paper, I first introduce what the ethical dilemma of autonomous vehicles is about. Second, I show how we could be able to assign legal responsibility for autonomous vehicles. Legal probability is the received criteria for causal responsibility most of the legal theorists consider. But it remains vague. I articulate the concept of legal probability in terms of the probabilitstic theory of individual level causality while considering how one can assign causal responsibility for autonomous vehicles. My theory of causal responsibility may help one to assign legal responsibility not just for autonomous vehicles but also for people.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.32-38
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• 1999

An autonomous mobile vehicle for transport system must plan optimal path in work envimnrent without human supervision and obstacle collision. This is to reach a destination without getting lost. In this paper, a genetic algorithm for globaI and local path planning and collision avoidance is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The sinmulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.rithms.