• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.93-103
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• 1999

To detect obstacles and lane-markers for driving vehicles, a new moving window scheme where moving windows are assigned to an image frame captured by a camera is addressed. For the detection of obstacles, it is important to estimate lane-markers precisely and rapidly. For this purpose, selecting some partes of an image frame at the expected lane locations, i.e., selecting window are generally adopted for extracting lane-markers efficiently. In this paper, a new scheme that extracts lane-markers precisely by assigning variable size windows at the expected locations of lane-markers considering the road curvature and finally detects obstacles within a driving lane is proposed. The accuracy improvement using this moving window scheme is showed by comparing to the conventional fixed window method and to using radar to laser sensors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1365-1373
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• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 pixel. This histogram is (x, y) value of pixel. For example, first line histogram intensity wave from (0, 0) to (0, 197) and last wave from (280, 0) to (2n, 197. So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.377-383
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• 2021

Recently, in accordance with the 4th industrial revolution, The use of autonomous mobile robots for flexible logistics transfer is increasing in factories, the warehouses and the service areas, etc. In large factories, many manual work is required to use Simultaneous Localization and Mapping(SLAM), so the need for the improved mobile robot autonomous driving is emerging. Accordingly, in this paper, an algorithm for mapless navigation that travels in an optimal path avoiding fixed or moving obstacles is proposed. For mapless navigation, the robot is trained to avoid fixed or moving obstacles through Deep Q Network (DQN) and accuracy 90% and 93% are obtained for two types of obstacle avoidance, respectively. In addition, DQN requires a lot of learning time to meet the required performance before use. To shorten this, the target size change algorithm is proposed and confirmed the reduced learning time and performance of obstacle avoidance through simulation.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.750-753
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• 2000

본 논문에서는 미지의 환경에서 이동 로봇이 주행 중 얻어진 격자지도(grid map)상의 장애물 정보를 이용하여 이동 로봇 주변환경을 직선선분으로 표현한다. 격자지도의 장애물 정보는 초음파 센서를 이용하여 얻어지므로 이동로봇과 인접한 장애물 정보만을 얻게된다. 얻어진 격자 정보를 호프변환을 이용하여 직선선분을 구축하고 이를 이전에 얻어진 직선선분과 결합하여 전체지도를 완성해 간다. 논의된 방법은 모의실험을 통하여 증명하였다.

• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.31-37
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• 2007

The importance of NPC's role in computer games is increasing. An NPC must perform its tasks by perceiving obstacles and other characters and by moving through them. It has been proposed to plan a natural-looking path against fixed obstacles by using a generalized visibility graph. In this paper we develop the execution module for an NPC to move efficiently along the path planned on the generalized visibility graph. The planned path consists of line segments and arc segments, so we define steering behaviors such as linear behaviors, circular behaviors, and an arriving behavior for NPC's movements to be realistic and utilize them during execution. The execution module also includes the collision detection capability to be able to detect dynamic obstacles and uses a decision tree to react differently according to the detected obstacles. The execution module is tested through the simulation based on the example scenario in which an NPC interferes the other moving NPC.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1153-1156
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• 1996

본 논문은 새로운 지역 경로 계획 알고리즘으로 DPH(Distance Profile Histogram)방법과 뉴럴네트워크를 사용한 주행 방법을 제안한다. DPH방법은 격자형 환경 모델을 기반으로 장애물의 존재 유무와 거리정보와 같은 장애물의 기하학적 배치정보를 사용하게 된다. 또한 긴 장애물이나 막힘상황(Dead end)과 같이 지역 경로 계획만으로는 회피하기 어려운 상황에서는 뉴럴네트워크에 의해 학습된 정보에 의해 주행하는 방법을 사용했다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.451-456
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• 2009

In this paper, a virtual force is generated and fed back to the operator to make the teleoperation more reliable, which reflects the relationship between a slave robot and an uncertain remote environment as a form of an impedance. In general, for the teleoperation, the teleoperated mobile robot takes pictures of the remote environment and sends the visual information back to the operator over the Internet. Because of the limitations of communication bandwidth and narrow view-angles of camera, it is not possible to watch certain regions, for examples, the shadow and curved areas. To overcome this problem, a virtual force is generated according to both the distance between the obstacle and the robot and the approaching velocity of the obstacle w.r.t the collision vector based on the ultrasonic sensor data. This virtual force is transferred back to the master (two degrees of freedom joystick) over the Internet to enable a human operator to estimate the position of obstacle at the remote site. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. It is demonstrated by experiments that this collision vector based haptic reflection improves the performance of teleoperated mobile robot significantly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1886-1887
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• 2011

본 논문은 군집 로봇 포메이션 이동 제어를 위한 방법을 제안한다. Potential field method 알고리즘을 이용하여 Leader-Bot의 장애물 회피와 이동 경로를 계획한다. Leader-bot을 기준으로 하는 Follewer-bot의 포메이션 형성을 위해 Formation generated function을 사용한다. Leader-bot과 Follower-bot들 간에 충돌회피와 Follower-bot들의 장애물 회피를 위해 Potential function을 적용한다. 제안한 방법은 시뮬레이션을 통하여 실제 운용 가능성을 검증한다.