• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.261-263
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• 2006

Nowadays, technologies such as RFID, sensor network makes our life comfortable more and more. In this paper we propose a wearable computing system for blind and deaf person who can be easily out of sight from our technology. We are making a wearable computing system that is consisted of embedded board to processing data, ultrasonic sensors to get distance data and motors that make vibration as a signal to see the screen for a deaf person. This system offers environmental informations by text and voice. For example, distance data from a obstacle to a person are calculated by data compounding module using sensed ultrasonic reflection time. This data is converted to text or voice by main processing module, and are serviced to a handicapped person. Furthermore we will extend this system using a voice recognition module and text to voice convertor module to help communication among the blind and deaf persons.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2444-2446
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• 2003

This paper presents identified locations of obstacles using ultrasonic and vision sensor for mobile robots. An ultrasonic and a vision sensor provide complementary information. To overcome limitations of each sensor, they are combined. To improve effectiveness of detecting of obstacles in image processing, a modified splitting/merging algorithm is proposed. In order to verify effectiveness, proposed algorithm is applied to a mobile robot control system.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.327-333
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• 2011

Intelligent robots are widely needed in various areas of industry from extremely dangerous environments to service tasks. For autonomous mobile robots, it is significant to move itself safely to a destination point, recognizing its surroundings. Advances in sensor technology and its applications are achieved in order to develop an intelligent robot. In this paper, a mobile robot with a path-finding algorithm is presented. The path-finding algorithm is the one that does not only find a path to designated destination and also recognizes obstacles on the way, calculating its distance. 10 ultrasonic sensor are mounted on the front and rear of the mobile robot to figure out its position. Specular reflection and wide viewing angle, which are inherent characteristics of ultrasonic waves, cause errors in measuring distance.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.210-218
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• 2021

CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.638-647
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• 1996

Robot manipulators for harvesting fruits must be controlled to track the desired path of end-effector to avoid obstacles under the consideration of collision free area and safety path. This paper presents a robot path control algorithm to secure a collision free area with the recognition of work environments. The flexible space, which does not damage fruits or branches of tree due to their flexibility and physical properties , extends the workspace. Now the task is to control robot path in the extended workspace with the consideration of collision avoidance and velocity limitation at the time of collision concurrently. The feasibility and effectiveness of the new algorithm for redundant manipulators were tested through simulations of a redundant manipulator for different joint velocities.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.187-195
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• 2024

Light detection and ranging (LiDAR), a widely used sensor in mobile robots and autonomous vehicles, has its most important function as measuring the range of objects in three-dimensional space and generating point clouds. These point clouds consist of the coordinates of each reflection point and can be used for various tasks, such as obstacle detection and environment recognition. However, several processing steps are required, such as three-dimensional modeling, mesh generation, and rendering. Efficient data processing is crucial because LiDAR provides a large number of real-time measurements with high sampling frequencies. Despite the rapid development of controller computational power, simplifying the computational algorithm is still necessary. This paper presents a method for estimating the presence of curbs, humps, and ground tilt using range measurements from a single horizontal or vertical scan instead of point clouds. These features can be obtained by data segmentation based on linearization. The effectiveness of the proposed algorithm was verified by experiments in various environments.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.759-764
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• 2011

This paper deals with the method of using the amended virtual force field technique to avoidance the front environment(wall, obstacles etc.) in navigating by using the environmental informations recognized by a ultrasonic-ring and pan/tilt CCD camera equipped on a mobile robot. we will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. It is proposed the rusult from the experimental run based on a virtual force field(VFF) method to support the validity of the aforementioned architecture of mobile service robot for local navigation and obstacle avoidance for autonomous mobile robots. We will conclude by discussing some possible future extensions of the project. The results show that the proposed algorithm is apt to identify obstacles in an indoor environments to guide the robot to the goal location safely.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.75-81
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• 2014

The integral image is the sum of input image pixel values. It is mainly used to speed up processing of a box filter operation, such as Haar-like features. However, large memory for integral image data can be an obstacle on an embedded hardware environment with limited memory resources. Therefore, an efficient method to store the integral image is necessary. In this paper, we propose a memory size reduction hardware design for integral image. The hardware design is used two methods. It is the new integral image memory and modulo calculation for reducing integral image data. The new integral image memory has additional calculation overhead, but it is not obstacle in hardware environment that parallel processing is possible. In the Xilinx Virtex5-LX330T targeted experimental result, integral image memory can be reduced by 50% on a $640{\times}480$ 8-bit gray-scale input image.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.113-123
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• 2000

In the navigation for a mobile robot, the collision avoidance with unexpected obstacles is essential for the safe navigation and it is independent of the technique used to control the mobile robot. This paper presents a new collision avoidance algorithm using neural network for the safe navigation of the autonomous mobile robot equipped with CAN and ultrasonic sensors. A tracked wheeled mobile robot has a stability and an efficiency to move on a rough ground. And its mechanism is simple. However it has difficulties to recognize its surroundings. Because the shape of the tracked wheeled mobile robot is a square type, sensor modules are generally located on the each plane surface of 4 sides only. In this paper, the algorithm using neural network is proposed in order to avoid unexpected obstacles. The important character of the proposed algorithm is to be able to detect the distance and the angle of inclination of obstacles. Only using datum of the distance and the angle, informations about the location and shape of obstacles are obtained, and then the driving direction is changed. Consequently, this algorithm is capable of real time processing and available for a mobile robot which has few sensor modules or the limited sensing range such as a tracked wheeled mobile robot. Effectiveness of the proposed algorithm is illustrated through a computer simulation and an experiment using a real robot.