• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.277-282
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• 2011

This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.983-988
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• 2011

This paper presents a robust method for ground plane detection in vision-based applications based on a monocular sequence of images with a non-stationary camera. The proposed method, which is based on the reliable estimation of the homography between two frames taken from the sequence, aims at designing a practical system to detect road surface from traffic scenes. The homography is computed using a feature matching approach, which often gives rise to inaccurate matches or undesirable matches from out of the ground plane. Hence, the proposed homography estimation minimizes the effects from erroneous feature matching by the evaluation of the difference between the predicted and the observed matrices. The method is successfully demonstrated for the detection of road surface performed on experiments to fill an information void area taken place from geometric transformation applied to captured images by an in-vehicle camera system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.36.4-36
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• 2001

A robust and reliable path recognition system is one necessary component for the autonomous navigation of a mobile robot to help determining its current position in its navigation map. This paper describes a computer visual path-recognition system using on-board video camera as vision-based driving assistance for an autonomous navigation mobile robot. The common problem for a visual system is that its reliability was often influenced by different lighting conditions. Here, two different image processing methods for the path detection were developed to reduce the effect of the luminance: one is based on the RGB color model and features of the path, another is based on the HSV color model in the absence of luminance.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.1017-1028
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• 2019

Pedestrian tracking is a particular object tracking problem and an important component in various vision-based applications, such as autonomous cars and surveillance systems. Following several years of development, pedestrian tracking in videos remains challenging, owing to the diversity of object appearances and surrounding environments. In this research, we proposed a tracking-by-detection system for pedestrian tracking, which incorporates a convolutional neural network (CNN) and color information. Pedestrians in video frames are localized using a CNN-based algorithm, and then detected pedestrians are assigned to their corresponding tracklets based on similarities between color distributions. The experimental results show that our system is able to overcome various difficulties to produce highly accurate tracking results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.197-205
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• 2006

This paper presents the moving object tracking method using vision system. In order to track object in real time, the image of moving object have to be located the origin of the image coordinate axes. Accordingly, Fuzzy Control System is investigated for tracking the moving object, which control the camera module with Pan/Tilt mechanism. Hereafter, so the this system is applied to mobile robot, we design and implement image processing board for vision system. Also fuzzy controller is implemented to the StrongArm board. Finally, the proposed fuzzy controller is useful for the real-time moving object tracking system by experiment.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.65-70
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• 2013

The integrated sensor module of vehicle combines the functions of rain sensor, auto defog sensor, and sun angle sensor into a single module. These functions originally were applied to work separatively. This integrated sensor module should meet the each performance which appears from the individual modules up to the same level or higher. Therefore, it is important to verify the stability and the accuracy considering the characteristics of the integrated sensor module according to various situations. For the verification, we need to use the actual data of integrated sensor module measured but, a lot of time and money is needed to collect data measured under various circumstances when operating. Thus, through the development of this simulator for the control of the integrated sensor module, we can use it effectively for the initial verification of integrated sensor module by implementing the various situations. In this paper, the simulator for controlling the integrated sensor module which combines vision-based rain sensor, auto defog sensor, auto light sensor, and sun angle sensor has been developed.

• Special Issue of the Society of Naval Architects of Korea
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• 2013.12a
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• pp.73-80
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• 2013

From broad point of view, seam tracking has been one of main issues with respect to welding automation. Several attempts have been successful for seam tracking of fixed weaving width. As a solution of the seam tracking methods for varying groove width, the visual sensors such as CCD cameras have been adopted. Although the vision sensing techniques can achieve high accuracy, the weak point is that well-prepared vision sensor environment should be required to obtain high-quality visual measurements which can be easily affected by significant noises in industrial areas. This paper proposed an alternative seam tracking algorithm for narrow groove. A special measurement device for arc voltage, in this study, is developed to enhance the reliability of the measured welding signals. Based on the developed arc sensor algorithm, an automatic weld-width tracking algorithm is also proposed, which is able to predict the weld-position more accurately. The usefulness of the automatic weld-width tracking algorithm was well verified by applying it to gas tungsten arc welding (GTAW).

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.384-391
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• 1998

When a device is mounted on the PCB, it is impossible to have zero defects due to many unpredictable problems. Among these problems, devices with bent corner leads due to mis-handling and which are not placed at a given point measured along the axis are principal problem in SMT(Surface Mounting Technology). It is obvious that given the complexity of the inspection task, the efficiency of a human inspection is questionable. Thus, new technologies for inspection of SMD(Surface Mounting Device) should be explored. An example of such technologies is the Automated Visual Inspection(AVI), wherein the vision system plays a key role to correct this problem. In implementing vision system, high-speed and high-precision are indispensable for practical purposes. In this paper, a new algorithm based on the Radon transform which uses a projection technique to inspect the FIC(Flat Integrated Circuit) device is proposed. The proposed algorithm is compared with other algorithms by measuring the position error(center and angle) and the processing time for the device image, characterized by line scan camera.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.164-171
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• 2010

We have studied the port-automation system which is requested by the steep increment of cost and complexity for processing the freight. This paper will introduce a new algorithm for navigating and controlling the autonomous Guided Vehicle (AGV). The camera has the optical distortion in nature and is sensitive to the external ray, the weather, and the shadow, but it is very cheap and flexible to make and construct the automation system for the port. So we tried to apply to the AGV for detecting and tracking the lane using the CCD camera. In order to make the error stable and exact, this paper proposes new concept and algorithm for obtaining the error is generated by the Virtual Photo-Sensor Array (VPSA). VPSAs are implemented by programming and very easy to use for the various autonomous systems. Because the load of the computation is light, the AGV utilizes the maximal performance of the CCD camera and enables the CPU to take multi-tasks. We experimented on the proposed algorithm using the mobile robot and confirmed the stable and exact performance for tracking the lane.