• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.62-74
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• 2020

Although the government and local governments devote efforts to activate bicycles, they only access to the supply infrastructure such as bike lanes and the public bicycle rental service centers without considering the measures to overcome the geographical constraints of slope. Therefore, this study constructs bicyclist's energy consumption estimation model through experimental methods of slope gradient and heart rate measurement and suggest the bicycle route choice model which could minimize the energy by the slope gradient. After calculating the RMSE of the estimated energy consumption by applying this model to the simulation section, it is confirmed to be 41% better than the model which does not reflect slope gradient. The results of this study are expected to be applied to the bicycle infrastructure planning that considers both longitude and transverse of bike lanes and the algorithm of bicycle route guidance system in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.79-84
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• 2021

The most important device of the AGV is the guide sensor, and the typical function of this sensor is high accuracy and extraction of the road. If the accuracy of the guide sensor is low or the sensor device is extracted the wrong track, this causes the problems such as the AGV collision, track-out, the load falling due to AGV swing. In order to improve these problems, this study is proposed a signal processing method of the guide sensor based on multi-maskings and the center of gravity method, and evaluated its performance. As a result, the proposed method showed that the mean error of absolute value is 2.32[mm] and it showed performance improvement of 27[%] than the center of gravity method of existence. Therefore, when the proposed signal processing method is applied, It is thought that the posture control and driving stability of the AGV will be improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.148-156
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• 2011

This paper presents an implementation of autonomous navigation of a mobile robot indoors. It explains methods for map building, localization, obstacle avoidance and path planning. Geometric map is used for localization and path planning. The localization method calculates sensor data based on the map for comparison with the real sensor data. Monte Carlo Localization(MCL) method is adopted for estimation of the robot position. For obstacle avoidance, an artificial potential field generates repulsive and attractive force to the robot. Dijkstra algorithm plans the shortest distance path from a start position to a goal point. The methods integrate into autonomous navigation method and implemented for indoor navigation. The experiments show that the proposed method works well for safe autonomous navigation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.97-100
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• 2023

차량 인터넷은 목적지까지 스스로 주행하는 자율 주행 자동차의 최적 경로 설정을 도와주는 차세대 네트워크이다. 자율 주행 자동차의 원활한 자율 주행을 위해서는 도로 위 객체 인지뿐만 아니라 실시간 교통 정보가 수신되어야 한다. 공격자는 자동차로 전달되는 메시지를 탈취하여 내용을 변경하거나 메시지를 제거하는 중간자 공격을 시도할 수 있다. 중간자 공격을 탐지하기 위해 MARINE 기법이 제안되었지만, 주행하는 자동차가 적은 환경에서 중간자 공격을 탐지하기 어렵다. 제안 방법은 이러한 문제를 해결하기 위해 교통 정보 센터에 축적된 교통 정보를 이용하여 자동차에 전달되는 메시지를 분석하고 중간자 공격을 탐지하는 방법을 제안한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.387-392
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• 2006

In the environment where AGVs(Automated Guided Vehicles) operate concurrently in limited space, collisions. deadlocks, and livelocks which have negative effect on the productivity of AGVs occure more frequently. The accelerated motion of an AGV is also the factor that make the AGV routing more difficult because the accelerated motion makes it difficult to estimate the vehicle's exact travel time. In this study, we propose methods of avoiding collisions, deadlocks, and livelocks using OAR(Occupancy Area Reservation) table, and selecting best route by estimating the travel time of an AGV in accelerated motion. A time-driven simulation validated the effectiveness of the proposed methods.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.606-608
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• 1999

본 논문에서는 이동 로봇의 유연하고 짧은 경로 계획을 위하여 기존의 그리드 셀(grid cell)로 구성되는 지도 대신에 삼각형을 이용하여 지도를 구성하는 새로운 방법을 제안한다. 기존의 그리드 셀로 구성되는 지도의 경우 이동 로봇가 현재 셀에서 다음 셀로 진행시 진행 방향이 8 방향이나, 본 논문에서 제안한 방법에 의해 구성된 새로운 지도는 셀을 삼각형으로 표현함으로써, 이동 로봇의 진행 방향이 12 방향이 된다. 이와 같이 이동 로봇의 진행 방향이 증가한다는 것은 이동 로봇이 더욱 유연하게 장애물을 회피하며 더욱 짧은 경로로 주행할 수 있는 가능성을 의미한다. 한편, 본 논문에서 제안한 삼각형 지도 작성 방법의 효율성을 기존의 그리드 셀을 이용한 경로 계획 알고리즘인 거리 변환(path transform) 경로 계획을 통하여 증명한다. 또한 새로운 삼각형 지도 구성이 메모리의 효율성 위해 이동 로봇의 주행 환경을 장애물이 비어있는 공간을 가능한 하나의 셀로 병합하는 4진트리 방법(quadtree method)에도 적용 가능함을 보인다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.265-275
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• 2023

The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.18-23
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• 2003

This paper presents new algorithms of path planning and obstacle avoidance for an autonomous mobile robot to navigate under unknown environments in the real time. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. It is shown by computer simulation that these algorithms are working well. Furthermore, an autonomous mobile robot was constructed to implement and test these algorithms in the real field. The experimental results are also satisfactory just like those of computer simulation.