• 제목/요약/키워드: 장애물인식

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A study on Simple and Complex Algorithm of Self Controlled Mobile Robot for the Obstacle Avoidance and Path Plan (자율 이동로봇의 장애물 회피 및 경로계획에 대한 간략화 알고리즘과 복합 알고리즘에 관한 연구)

  • 류한성;최중경;구본민;박무열;권정혁
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.1
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    • pp.115-123
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    • 2002
  • In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance and path plan. One 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 TMS320F240 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 95 percent filled screen from input image. And the robot recognizes obstacle about 95 percent filled something, so it could avoid the obstacle and conclude new path plan. Another is complex algorithm that image preprocessing by edge detection, converting, thresholding and image processing by labeling, segmentation, pixel density calculation.

Autonomous Wheelchair System Using Gaze Recognition (시선 인식을 이용한 자율 주행 휠체어 시스템)

  • Kim, Tae-Ui;Lee, Sang-Yoon;Kwon, Kyung-Su;Park, Se-Hyun
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.4
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    • pp.91-100
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    • 2009
  • In this paper, we propose autonomous intelligent wheelchair system which recognize the commands using the gaze recognition and avoid the detected obstacles by sensing the distance through range sensors on the way to driving. The user's commands are recognized by the gaze recognizer which use a centroid of eye pupil and two reflection points extracted using a camera with infrared filter and two infrared LEDs. These are used to control the wheelchair through the user interface. Then wheelchair system detects the obstacles using 10 ultrasonic sensors and assists that it avoid collision with obstacles. The proposed intelligent wheelchair system consists of gaze recognizor, autonomous driving module, sensor control board and motor control board. The gaze recognizer cognize user's commands through user interface, then the wheelchair is controled by the motor control board using recognized commands. Thereafter obstacle information detected by ultrasonic sensors is transferred to the sensor control board, and this transferred to the autonomous driving module. In the autonomous driving module, the obstacles are detected. For generating commands to avoid these obstacles, there are transferred to the motor control board. The experimental results confirmed that the proposed system can improve the efficiency of obstacle avoidance and provide the convenient user interface to user.

Local Path Planning and Obstacle Avoidance System based on Reinforcement Learning (강화학습 기반의 지역 경로 탐색 및 장애물 회피 시스템)

  • Lee, Se-Hoon;Yeom, Dae-Hoon;Kim, Pung-Il
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.01a
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    • pp.59-60
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    • 2019
  • WCS에서 AGV의 스케줄링과 동적, 정적 장애물 인식 및 충돌 회피문제는 오래전부터 다뤄져 온 중요한 문제이다. 본 논문에서는 위의 문제를 해결하기 위해 Lidar 센서를 중심으로 다양한 데이터를 기반으로 한 강화학습 시스템을 제안한다. 제안하는 시스템은 기본의 명시적인 알고리즘에 비해 다양하고 유동적인 환경에서 경로 계획과 동적 정적 장애물을 인식하고 안정적으로 회피하는 것을 확인하였으며 산업 현장에 도입 가능성을 확인하였다. 또한 강화학습의 적용 범위, 적용 방안과 한계에 대해서 시사한다.

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Obstacle Avoidance of Indoor Mobile Robot using RGB-D Image Intensity (RGB-D 이미지 인텐시티를 이용한 실내 모바일 로봇 장애물 회피)

  • Kwon, Ki-Hyeon;Lee, Hyung-Bong
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.10
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    • pp.35-42
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    • 2014
  • It is possible to improve the obstacle avoidance capability by training and recognizing the obstacles which is in certain indoor environment. We propose the technique that use underlying intensity value along with intensity map from RGB-D image which is derived from stereo vision Kinect sensor and recognize an obstacle within constant distance. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it. From the comparison experiment between RGB-D data and intensity data, RGB-D data got 4.2% better accuracy rate than intensity data but intensity data got 29% and 31% faster than RGB-D in terms of training time and intensity data got 70% and 33% faster than RGB-D in terms of testing time for LDA and SVM, respectively. So, LDA, SVM have good accuracy and better training/testing time to use for obstacle avoidance based on intensity dataset of mobile robot.

Image processing algorithm for preceding vehicle detection based on DLI (선형차량 인식을 위한 DLI 기반의 영상처리 알고리즘)

  • Hwang, H.J.;Baek, H.R.;Yi, U.K.
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2459-2461
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    • 2003
  • 본 논문은 차량 내에 설치된 두 대의 CCD 카메라를 이용하여 도로 영상으로부터 주행차선내에 있는 장애물을 인식하는 새로운 알고리즘을 제시한다. 제안된 알고리즘은 주행하는 차선과 관련이 있는 차선 정보만을 이용하여, 스테레오 영상에서 변이도를 추출할 수 있는 변이도 함수인 DLI(Disparity of lane-related information)를 정의하였다. DLI는 선행 차량과 같은 장애물은 주위보다 상대적으로 큰 에지값을 가진다는 특성을 이용하여, 주행차선 내에 있는 장애물의 유무를 검출하고 위치를 유추한다. 제안된 방법은 특징점의 탐색공간을 현저히 줄여 실시간 처리문제를 해결한 수 있는 장점을 가지고 있다. 본 논문에서는 DLI를 이용한 선행차량 인식기법의 성능을 검증하기 위하여 다양한 환경의 도로영상에 알고리즘을 적용하여 제안한 방법의 우수함을 확인하였다.

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A study on the Obstacle-Avoidance Walking Algorithm of a Biped Robot (이족보행로봇의 장애물 극복 보행알고리즘에 관한 연구)

  • 김용태;이은선;이희영
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09b
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    • pp.1-4
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    • 2003
  • 인간의 작업을 보조 혹은 대신하기 위해서 인간과 흡사한 이족보행로봇에 대한 연구가 많이 진행되고 있다. 이족보행로봇이 인간을 대신해서 어떤 작업을 하기 위해서는 작업공간에서의 자유로운 이동과 장애물 대처능력은 반드시 필요한 기능이다. 본 논문에서는 안정된 정적보행 및 장애물을 지능적으로 대처하는 이족보행로봇의 보행알고리즘을 제안하였다. 먼저 장애물 대처가능한 이족보행로봇의 기구 설계 및 제어기 구현에 대하여 설명하고, 인간의 보행 분석 결과를 바탕으로 안정된 정적보행 알고리즘을 제안하였다. 또한 좌우 회전 및 옆걸음을 통한 장애물 회피 알고리즘, 발에 부착된 적외선센서로 장애물을 인식하여 장애물을 넘어가는 보행 알고리즘을 제안하였다. 제안한 보행알고리즘은 이족보행로봇을 제작하여 다양한 작업환경에서 실험으로 성능을 검증하였다.

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A Study on Obstacle Detection of Vacuum Cleaner Using Neural Network (신경망을 이용한 청소로봇의 장애물 판단에 관한 연구)

  • Lee, Sang-Hyoung;Yi, Keon-Young
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.1921-1922
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    • 2006
  • 청소 로봇의 장애물 판단은 청소 로봇이 정확하고 빠르게 장애물을 파악하여 정밀한 제어를 수행하며 청소 효율을 향상 시키는데 중요하다. 청소 로봇이 장애물을 판단하는데 여러 가지 알고리즘이 있지만 신경망 알고리즘 특히, BP(Back-Propagation) 알고리즘을 적용하여 장애물 인식에 있어 반복학습 시키면 청소 로봇은 보다 빠르고 정착하게 장애물을 스스로 판단 할 수 있다. 본 논문에서는 청소 로봇에 부착된 초음파 센서와 장애물과의 거리데이터를 얻어, 이를 BP 알고리즘에 적용하는 것을 연구하며 학습률, 반복학습, 최대 제곱 오차값를 조정한 실험결과로 특성변화를 관찰하고 해석하여 검증한다.

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Detection of a Land and Obstacles in Real Time Using Optimal Moving Windows (최적의 Moving Window를 사용한 실시간 차선 및 장애물 감지)

  • Choi, Sung-Yug;Lee, Jang-Myung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.3
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    • pp.57-69
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    • 2000
  • A moving window technique for detecting a lane and obstacles using the Images captured by a CCD camera attached in an automobile, is proposed in this paper To process the dynamic images in real time, there could be many constraints on the hardware To overcome these hardware constraints and to detect the lane and obstacles in real time, the optimal size of window IS determined based upon road conditions and automobile states. By utilizing the sub-Images inside the windows, detection of the lane and obstacles become possible m real time. For each Image frame, the moving windows are re-determined following the predicted directions based on Kalman filtering theory to Improve detection accuracy, as well as efficiency The feasibility of proposed algorithm IS demonstrated through the simulated experiments of highway driving.

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Automatic Walking Guide for Visually Impaired People Utilizing an Object Recognition Technology (객체 인식 기술을 활용한 시각장애인 자동 보행 안내)

  • Chang, Jae-Young;Lee, Gyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.2
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    • pp.115-121
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    • 2022
  • As city environments have recently become crowded, there are many obstacles that interfere with the walking of the visually impaired on pedestrian roads. Typical examples include ballads, parking breakers and standing signs, which usually do not get in the way, but blind people may be injured by collisions. To solve such a problem, many solutions have been proposed, but they are limited in applied in practical environments due to the several restrictions such as outside use only, inaccurate obstacle sensing and requirement of special devices. In this paper, we propose a new method to automatically detect obstacles while walking on the pedestrian roads and warn the collision risk in advance by using only sensors embedded in typical mobile phones. The proposed method supports the walking of the visually impaired by notifying the type of obstacles appearing in front of them as well as the distance remaining from the obstacles. To accomplish this goal, we utilized an object recognition technology applying the latest deep learning algorithms in order to identify the obstacles appeared in real-time videos. In addition, we also calculate the distance to the obstacles using the number of steps and the pedestrian's stride. Compared to the existing walking support technologies for the visually impaired, our proposed method ensures efficient and safe walking with only simple devices regardless of the places.

A Study on the Obstacle-Avoidance Walking Algorithm of a Biped Robot (이족보행로봇의 장애물극복 보행알고리즘에 관한 연구)

  • Kim, Yong-Tae;Lee, Eun-Seon;Lee, He-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.686-691
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    • 2003
  • In the paper, an intelligent biped walking robot that can overcome the obstacle is developed. Walking algorithms are designed based on the analysis of the human's manner of walking. Infrared sensors are used to detect the obstacles in the working environment and the remote controller of the biped robot use a RF module. The experiment results show that the developed biped walking robot can perform the stable static walking, attention walking, rotation and side stepping to avoid the obstacle, and hurdling the obstacle using the distance correction algorithm that is designed based on the distance information between the biped robot and the obstacle.