• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.7
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• pp.611-619
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• 2016

This paper proposes a collision prevention system for an agricultural unmanned helicopter. The collision prevention system consists of an obstacle detection system, a mapping algorithm, and a collision avoidance algorithm. The obstacle detection system based on a LiDAR sensor is implemented in the unmanned helicopter and acquires distance information of obstacles in real-time. Then, an obstacle mapping is carried out by combining the distance to the obstacles with attitude/location data of the unmanned helicopter. In order to prevent a collision, alert is activated to an operator based on the map when the vehicle approaches to the obstacles. Moreover, the developed collision prevention system is verified through flight test simulating a flight pattern aerial spraying.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.552-557
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• 2009

In this paper, we propose hybrid navigation system, for obstacle detection and avoidance in Intelligent wheelchairs (IWs). To robustly detect obstacles and avoid them on various environments, hybrid navigation system combines both range-sensor and camera information. For this, 10 range-sensors (2 ultrasonic and 8 infra-red sensors) and CCD camera are used. Through processing the informations obtained from those sensors, our system can detect obstacles with various sizes and shapes, and then avoid them. To assess the effectiveness of the proposed hybrid navigation system, it was tested on complex environments including various obstacles, then the results showed the potential of our system as mobility aids for disabled people.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.614-619
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• 2013

In multi-robot systems, ultrasonic sensors are widely used for localization and/or obstacle detection. However, conventional ultrasonic sensors have a drawback, that is, the interference problem among ultrasonic transmitters. There are some previous studies to avoid interferences, such as TDMA (Time Division Multiple Access) and CDMA (Code Division Multiple Access). In multiple autonomous mobile robots systems, the Doppler-effect has to be considered because ultrasonic transceivers are attached to the moving robots. To overcome this problem, we find out the ASK (Amplitude Shift Keying)-CDMA technique is more robust to the Doppler-effect than the BPSK (Binary Phase Shift Keying)-CDMA technique. In this paper, we propose a new code-expression method and a Monte-Carlo based algorithm that optimizes the ultrasonic code combination in the ASK-CDMA ultrasonic system. The experimental results show that the proposed algorithm improves the performance of the ultrasonic multiple accessing capacity in the ASK-CDMA ultrasonic system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.163-173
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• 2013

We present a new computer vision technique which can detect unexpected or static vertical objects in road driving environment. We first obtain temporal and spatial difference images in each frame of a stereo video sequence. Using the difference images, we then generate VO and HO maps by improving the conventional V and H disparity maps. From the VO and HO maps, candidate areas of vertical obstacles on the road are detected. Finally, the candidate areas are merged and refined to detect vertical obstacles.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.6
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• pp.711-720
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• 2015

Recently many studies of Radar systems mounted on ground vehicles for autonomous driving, SLAM (Simultaneous localization and mapping) and collision avoidance have been reported. Since several pixels per an object may be generated in a close-range radar application, a width of an object can be estimated automatically by various signal processing techniques. In this paper, we tried to attempt to develop an algorithm to estimate obstacle width using Radar images. The proposed method consists of 5 steps - 1) background clutter reduction, 2) local peak pixel detection, 3) region growing, 4) contour extraction and 5)width calculation. For the performance validation of our method, we performed the test width estimation using a real data of two cars acquired by commercial radar system - I200 manufactured by Navtech. As a result, we verified that the proposed method can estimate the widths of targets.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1551-1560
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• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3270-3294
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• 2020

Some things come easily to humans, one of them is the ability to navigate around. This capability of navigation suffers significantly in case of partial or complete blindness, restricting life activity. Advances in the technological landscape have given way to new solutions aiding navigation for the visually impaired. In this paper, we analyze the existing works and identify the challenges of path selection, context awareness, obstacle detection/identification and integration of visual and nonvisual information associated with real-time assisted mobility. In the process, we explore machine learning approaches for robotic path planning, multi constrained optimal path computation and sensor based wearable assistive devices for the visually impaired. It is observed that the solution to problem is complex and computationally intensive and significant effort is required towards the development of richer and comfortable paths for safe and smooth navigation of visually impaired people. We cannot overlook to explore more effective strategies of acquiring surrounding information towards autonomous mobility.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.601-604
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• 2021

본 논문에서는 모바일 디바이스의 카메라로부터 얻은 RGB이미지를 분석하여 장애물을 안정적으로 탐지할 수 있는 프레임워크를 제안한다. 본 논문에서는 장애물을 안정적으로 찾기 위해 RANSAC(Random Sample Consensus)기반의 다중 평면 방식을 이용한 위험감지 시스템을 제안한다. 우리의 접근 방식은 RGB영상으로부터 특징점(Feature point)을 추출하고, 특징점을 분석(Feature point analysis)하여 영상내의 평면을 감지한다. 복잡한 지형으로 인해 생성되는 다수의 평면을 RANSAC을 통해 단일 평면으로 정규화하고, 이로부터 특징점을 분류하기 위한 기준점을 계산한다. 모바일 디바이스의 위치와 회전 제약 없이 효과적으로 기준평면(Reference plane)을 탐색할 수 있고, 영상 내 특징점을 실시간으로 계산한다. 다양한 실험을 통해 기준평면과 장애물과의 거리를 파악하여 장애물을 효과적으로 분류하는 결과를 얻었다. 우리의 기법은 실세계에서의 위험요소를 감지하고 모바일 디바이스 사용자의 안전성 확보에 활용할 수 있을 거라 기대한다.

• Aerospace Engineering and Technology
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• v.3 no.1
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• pp.242-250
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• 2004

This paper describes the detection method of wire-like obstacles using millimeter-wave radar system. Passive sensor like CCD camera can be used for the detection of high power electric cables on the hills or mountains and it can give very good quality of obstacle target information. But this system is very limited to use by bad weather condition. The detection capability for different diameters of wire targets using millimeter radar system have been accomplished. To simulate the target on the moving helicopter, rotating targets are used with fixed radar system. In the experiment 11mm, 16mm and 22mm diameter of wires have been detected in single, two and three wires in one position. The detected signal from single wire was very clear on gray level image. Three wires placed very closely together could be recognized in range, cross range image plane. For two and three wires, blur effect due to mutual scattering effect is observed.