• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.896-902
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• 2007

This paper proposes a vision-based kinematic control method for mobile robots with camera-on-board. In the previous literature on the control of mobile robots using camera vision information, the forward velocity is set to be a constant, and only the rotational velocity of the robot is controlled. More efficient motion, however, is needed by controlling the forward velocity, depending on the position in the corridor. Thus, both forward and rotational velocities are controlled in the proposed method such that the mobile robots can move faster when the comer of the corridor is far away, and it slows down as it approaches the dead end of the corridor. In this way, the smooth turning motion along the corridor is possible. To this end, visual information using the camera is used to obtain the perspective lines and the distance from the current robot position to the dead end. Then, the vanishing point and the pseudo desired position are obtained, and the forward and rotational velocities are controlled by the LOS(Line Of Sight) guidance law. Both numerical and experimental results are included to demonstrate the validity of the proposed method.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.169-176
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• 2012

GPS(Global Positioning System) is widely used for the position estimation of an aerial vehicle. However, GPS may not be available due to hostile jamming or strategic reasons. A vision-based position estimation method can be effective if GPS does not work properly. In mountainous areas without any man-made landmark, a horizon is a good feature for estimating the position of an aerial vehicle. In this paper, we present a new method to estimate the position of the aerial vehicle equipped with a forward-looking infrared camera. It is assumed that INS(Inertial Navigation System) provides the attitudes of an aerial vehicle and a camera. The horizon extracted from an infrared image is compared with horizon models generated from DEM(Digital Elevation Map). Because of a narrow field of view of the camera, two images with a different camera view are utilized to estimate a position. The algorithm is tested using real infrared images acquired on the ground. The experimental results show that the method can be used for estimating the position of an aerial vehicle.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2341-2343
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• 2002

This paper describes a vision-based line recognition and control of driving direction for an AGV(autonomous guided vehicle). As navigation guide, black stripe attached on the corridor is used. Binary image of guide stripe captured by a CCD camera is used. For detect the guideline quickly and extractly, we use for variable thresholding algorithm. this low-cost line-tracking system is efficiently using pc-based real time vision processing. steering control is studied through controller with guide-line angle error. This method is tested via a typical agv with a single camera in laboratory environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1099-1110
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• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.400-405
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• 2009

A new method for the catadioptric omnidirectional stereo vision with single camera is presented in this paper. The proposed method uses a concave lens with a convex mirror. Since the optical part of the proposed method is simple and commercially available, the resultant omnidirectional stereo system becomes versatile and cost-effective. The closed-form solution for 3D distance computation is presented based on the simple optics including the reflection and the reflection of the convex mirror and the concave lens. The compactness of the system and the simplicity of the image processing make the omnidirectional stereo system appropriate for real-time applications such as autonomous navigation of a mobile robot or the object manipulation. In order to verify the feasibility of the proposed method, an experimental prototype is implemented.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.192-197
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• 2009

In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.291-302
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• 1998

A digital image processing technique which is able to be used for getting the velocity vector distribution of a surface of the spilt oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.8
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• pp.671-677
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• 2017

A new INS/Vision integrated navigation system by using multi-vision sensors is addressed in this paper. When the total number of landmark measured by the vision sensor is smaller than the allowable number, there is possibility that the navigation filter can diverge. To prevent this problem, multi-vision concept is applied to expend the field of view so that reliable number of landmarks are always guaranteed. In this work, the orientation of camera installed are 0, 120, and -120degree with respect to the body frame to improve the observability. Finally, the proposed technique is verified by using numerical simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.245-246
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• 2014

This paper suggests the navigation information display system which is based on augmented reality technology and especially focuses on image analysis technology. Navigator has to always confirm the information from marine electronic navigation devices and then they compare with the view of outside targets of the windows. During this 'head down' posture, they feel uncomfortable and sometimes it cause near-accidents such as collision or missing objects, because he or she cannot keep an eye on the front view of windows. Augmented reality can display both of information of virtual and real in a single display. Therefore we tried to adapt the AR technology to help navigators and have been studied and developed image pre-processing module as a previous research already. To analysis the outside view of the bridge window, we have extracted navigational information from the camera image by using image processing. This paper mainly describes about recognizing ship feature by haar-like feature and filtering region of interest area by AIS data, which are to improve accuracy of the image analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.835-854
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• 2012

In this paper, we propose a novel positioning system for indoor navigation which helps a user navigate easily to desired destinations in an unfamiliar indoor environment using his mobile phone. The system requires only the user's mobile phone with its basic equipped sensors such as a camera and a compass. The system tracks user's positions and orientations using a vision-based approach that utilizes $360^{\circ}$ panoramic images captured in the environment. To improve the robustness of the vision-based method, we exploit a digital compass that is widely installed on modern mobile phones. This hybrid solution outperforms existing mobile phone positioning methods by reducing the error of position estimation to around 0.7 meters. In addition, to enable the proposed system working independently on mobile phone without the requirement of additional hardware or external infrastructure, we employ a modified version of a fast and robust feature matching scheme using Histogrammed Intensity Patch. The experiments show that the proposed positioning system achieves good performance while running on a mobile phone with a responding time of around 1 second.