• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.824-826
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• 2022

매년 쓰레기 발생량이 증가하는 시대에서 청소로봇의 중요성이 크게 떠오르고 있다. 이에 노면 청소에 집중되어 있는 기존 청소로봇과 달리 본 연구는 쓰레기를 수거하는 방식의 청소로봇을 제시한다. 딥 러닝을 이용한 자율주행 쓰레기통 로봇은 Computer Vision 을 이용하여 쓰레기를 인식하고 자체 제작한 로봇 arm 을 이용하여 수거하며, 장애물을 피해 자율 주행하는 청소 서비스를 제공한다.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.56-63
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• 2003

This paper introduces a vision based autonomous mini mobile robot that is an approach to produce real autonomous vehicle. Previous autonomous vehicles are dependent on PC, because of complexity of designing hardware, difficulty of installation and abundant calculations. In this paper, we present an autonomous motile robot system that has abilities of accurate steering, quick movement in high speed and intelligent recognition as a stand-alone system using a mono camera. The proposed system has been implemented on mini track of which width is 25~30cm, and length is about 200cm. Test robot can run at average 32.9km/h speed on straight lane and average 22.3km/h speed on curved lane with 30~40m radius. This system provides a model of autonomous mobile robot adapted a lane recognition algorithm in odor to make real autonomous vehicle easily.

• Tunnel and Underground Space
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• v.30 no.1
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• pp.76-86
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• 2020

In this study, a small autonomous driving robot was developed for underground mines using the Light Detection and Ranging (LiDAR) sensor. The developed robot measures the distances to the left and right wall surfaces using the LiDAR sensor, and automatically controls its steering to drive along the centerline of mine tunnel. A field experiment was conducted in an underground amethyst mine to test the driving performance of developed robot. During five repeated driving tests, the robot showed stable driving performance overall. There were no collision accidents with the wall of mine tunnel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.205-213
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• 2017

This paper is a study on the method to derive the functional level required for autonomous unmanned ground vehicle, one of the defense robots. Conventional weapon systems are not significantly affected by the operating environment, while defense robots exhibit different performance depending on the operating environment, even if they are on the same platform. If the performance of defense robot is different depending on operational environment, results of mission performance will be vary significantly. Therefore, it is necessary to clarify the level of function required by the military in order to research and develop most optimal defense robots. In this thesis, we propose a method to derive the required function level of unmanned ground vehicles, focusing on autonomous driving, one of the most vital functions of defense robots. Our results showed that the autonomous driving function depending intervention levels and evaluated functional sensitivity for autonomous driving of the unmanned vehicle using climate and topography as variables.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.802-805
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• 2019

본 논문은 이동로봇의 H/W에 관한 연구로서, 기존의 비평탄 지형의 자율주행 로봇이 수행하기 힘든 영역을 보완하기 위해 캐터필러 바퀴 기반의 플리퍼를 장착해 사물의 습득과 운반 기능을 적용함으로써 보다 정확한 주행 능력을 향상하는 방법을 제시한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.565-570
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• 2021

Agriculture in South Korea is losing productivity due to the lack of manpower as aging population increases. To overcome this, the agricultural robot market is growing rapidly, and research is being conducted on remote control and autonomous driving of agricultural robots. This work designs the appearance and structure of agricultural robots and implements the devices and control systems for driving. By utilizing and optimizing LiDAR sensors, we applied object recognition technology, which is an essential function for autonomous driving. This can reduce labor costs and improve productivity of transportation tasks that require the most labor in agriculture.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.312-313
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• 2007

본 논문은 자율주행로봇의 경로계획문제를 효율적으로 해결하기 위한 방법을 제안한다. 제안된 방법은 초기경로 생성과정과 초기경로를 개선하는 두 단계의 과정으로 구성된다. 효율적인 경로를 생성하기 위해서 최적화 문제를 해결하는 방법으로 잘 알려진 Dijkstra 알고리즘과 동적계획법(Dynamic Plogramming)을 적용한다. 그리고 제안된 방법의 효율성은 기존에 사용되는 경로계획 방법들과의 비교 시뮬레이션을 통해서 확인한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.219-222
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• 2002

본 논문에서는 미지의 환경에서 이동로봇의 자율 주행이 가능하도록 비전 시스템과 퍼지규칙을 이용한 경로 설정과 장애물 회피를 위한 알고리즘을 소개 하고자 한다. 한편 원격지에서도 로봇의 움직임을 파악할 수 있도록 인터넷을 통한 원격운용 기능을 추가함으로써 로봇의 효율적인 운용이 가능하도록 하였다. 소벨 연산자를 이용한 장애물의 윤곽선 추출과 퍼지규칙을 이용하여 경로 계획과 장애물 회피를 위한 알고리즘을 생성하였으며, 컴퓨터 시뮬레이션으로 그 효율성을 검증하였다. 또한 실제 이동 로봇을 제작하여 실험한 결과에서도 제안된 알고리즘이 우수한 성능을 발휘함을 확인할 수 있었다.

• ICROS
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• v.10 no.1
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• pp.48-52
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• 2004

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.107-114
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• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.