• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2774-2776
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• 2005

본 논문에서는 이동로봇에 삼차원 레이저 스캐너를 장착하여 삼차원 데이터의 수집, 수집된 데이터의 정합, 데이터 수집을 위한 이동로봇의 경로계획 및 장애물 회피주행 등 모든 작업들을 유기적으로 결합시켜 실내 환경에 다한 삼차원 모델을 자율제작하는 시스템을 제안한다. 이를 위해 스캔순서최적화를 통한 빠른 동적 물체 정보의 제거, 계층적 육면체 맵과 기하학적맵을 이용한 최적 경로 예측에 의한 다음 스캐닝 위치의 결정, 오도미터 정보와 명암 정보를 이용해 수정된 ICP 알고리즘을 통한 데이터의 정합을 통하여 이동물체와 관계없는 실내환경에 대한 삼차원 모델의 자율복원 한다.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.128-136
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• 2013

Recently, the localization recognition system research has been studied using various sensors according to increased interest in autonomous navigation flight. In case of indoor environment which cannot support GPS information, we have to look for another way to recognize current position. The Image-based localization recognition system has been interested although there are lots of way to know current pose. In this paper, we explain the localization recognition system based on mark and implementation of autonomous navigation flight. In order to apply to real environment which cannot support marks, localization based on real-time 3D map building is discussed.

• Journal of KSNVE
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• v.5 no.2
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• pp.158-162
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• 1995

자동차의 소음은 차실내 소음과 차외소음의 두가지로 나눌 수 있는데 소음은 자동차에 탑승하고 있는 사람들이 감성적으로 느끼는 것이어서 차량의 상품성에 직접적인 영향을 미치므로 자동차 제작자는 보다 더 정숙한 차실내 분위기를 만들기 위하여 자율적이 노력을 게을리 하지 않는 분야이며, 차외 소음은 산업화와 경제적 성장에 따른 자동차 수의 증가로 인하여 도로교통 소음에 크게 기여하므로 각국 정부 는 법률로써 이를 규제하고 있다. 소음을 포함한 환경오염 방지에 대한 관심이 고조 되는 가운데 도로 주변에서의 도로교통 소음은 주민의 일상생활 및 주게에 점점 더 크게 영향을 주게 되어, 국민이 소음측면에서 보다 더 편안한 생활을 할 수 있도록 정부는 가속주행소음, 배기소음, 경적소음 등 자동차로 기인하는 소음의 수준을 낮추고자 노력하여 왔다. 이 글에서 법규의 규제를 받고 있는 자동차로 기인하는 소음 중 도로교통소음에 기어가 큰 주행상태의 자동차 소음저감을 목표로 하는 가속 주행 소음 규제와 그 대책을 기술하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.11-18
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• 2021

We propose a method that combines learning in a virtual environment and a real environment for indoor autonomous driving through reinforcement learning. In case of learning only in the real environment, it takes about 80 hours, but in case of learning in both the real and virtual environments, it takes 40 hours. There is an advantage in that it is possible to obtain optimized parameters through various experiments through fast learning while learning in a virtual environment and a real environment in parallel. After configuring a virtual environment using indoor hallway images, prior learning was carried out on the desktop, and learning in the real environment was conducted by connecting various sensors based on Jetson Xavier. In addition, in order to solve the accuracy problem according to the repeated texture of the indoor corridor environment, it was possible to determine the corridor wall object and increase the accuracy by learning the feature point detection that emphasizes the lower line of the corridor wall. As the learning progresses, the experimental vehicle drives based on the center of the corridor in an indoor corridor environment and moves through an average of 70 steering commands.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.759-764
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• 2011

This paper deals with the method of using the amended virtual force field technique to avoidance the front environment(wall, obstacles etc.) in navigating by using the environmental informations recognized by a ultrasonic-ring and pan/tilt CCD camera equipped on a mobile robot. we will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. It is proposed the rusult from the experimental run based on a virtual force field(VFF) method to support the validity of the aforementioned architecture of mobile service robot for local navigation and obstacle avoidance for autonomous mobile robots. We will conclude by discussing some possible future extensions of the project. The results show that the proposed algorithm is apt to identify obstacles in an indoor environments to guide the robot to the goal location safely.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.29-39
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• 2019

As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

• Journal of Platform Technology
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• v.11 no.2
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• pp.26-38
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• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1370-1374
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• 2013

The suitcase can follow its owner all on its own via the Bluetooth connectivity in your phone. A robotic vacuum cleaner than can understand voice commands and even follow homeowner. Robots are used in a variety of applications such as a robot wheelchair. In this paper, I focus the problem of automatic return to the base in the process of developing the moving robot for loading things. In this paper, I propose the indoor localization method which is able to determine the position of the robot in the building by using image processing techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.194-210
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• 2023

LiDAR plays a key role in autonomous vehicles, where it is used to detect the environment in place of the driver's eyes, and its role is expanding. In recent years, there has been a growing need to test the performance of LiDARs installed in autonomous vehicles. Many LiDAR performance tests have been conducted in simulated and indoor(lab) environments, but the number of tests in outdoor(field) and real-world road environments has been minimal. In this study, we compared LiDAR performance under the same conditions lab and field to determine the relationship between lab and field tests and to establish the characteristics and roles of each test environment. The experimental results showed that LiDAR detection performance varies depending on the lighting environment (direct sunlight, led) and the detected object. In particular, the effect of decreasing intensity due to increasing distance and rainfall is greater outdoors, suggesting that both lab and field experiments are necessary when testing LiDAR detection performance on objects. The results of this study are expected to be useful for organizations conducting research on the use of LiDAR sensors and facilities for LiDAR sensors.