• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.9-15
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• 2021

It is a challenge for visually impaired people to access unfamiliar environments independently, hence the quality of life is reduced, and safety of life is compromised. An accurate and reliable door detection system comprising of way finding and indoor navigation can be beneficial for a large number of autonomous and mobile applications for visually impaired people. This paper illustrates an image-based door detection scheme for visually impaired people using stable features (edges and corners) including color averaging and image resizing. Simulation results show that the proposed scheme shows a significant improvement when compared with existing scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1011-1019
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• 2005

In this paper, Ubiquitous Home Mess-Cleanup Robot(UHMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of tile self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulate,, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and UHMR. Finally, the good performance of the designed UHMR is confirmed through the results of the mess clean-up and arrangement.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1612-1616
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• 2005

In this paper, a Home Mess-Cleanup Robot(HMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of the self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulator, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and HMR. Finally, the good performance of the designed HMR is confirmed through the results of the mess clean-up and arrangement.

• Korean Journal of Optics and Photonics
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• v.29 no.5
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• pp.204-214
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• 2018

Since LIDAR is advantageous for accurate information acquisition and realization of a high-resolution 3D image based on characteristics that can be precisely measured, it is essential to autonomous navigation systems that require acquisition and judgment of accurate peripheral information without user intervention. Recently, as an autonomous navigation system applying LIDAR has been utilized in human living space, it is necessary to solve the eye-safety problem, and to make reliable judgment through accurate obstacle recognition in various environments. In this paper, we construct a single-shot LIDAR system (SSLs) using a 1550-nm eye-safe light source, and report the analysis method and results of LIDAR signals for various measurement environments, reflective materials, and material angles. We analyze the signals of materials with different reflectance in each measurement environment by using a 5% Al reflector and a building wall located at a distance of 25 m, under indoor, daytime, and nighttime conditions. In addition, signal analysis of the angle change of the material is carried out, considering actual obstacles at various angles. This signal analysis has the merit of possibly confirming the correlation between measurement environment, reflection conditions, and LIDAR signal, by using the SNR to determine the reliability of the received information, and the timing jitter, which is an index of the accuracy of the distance information.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.667-675
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• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.4
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• pp.343-352
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• 2016

A multi-rotor vehicle is an unmanned vehicle consisting of multiple rotors. A multi-rotor vehicle can be categorized as tri-, quad-, hexa-, and octo-rotor depending on the number of the rotors. Multi-rotor vehicles have many advantages due to their agile flight capabilities such as the ability for vertical take-off, landing and hovering. Thus, they can be widely used for various applications including surveillance and monitoring in urban areas. Since multi-rotors are subject to uncertain environments and disturbances, it is required to implement robust attitude stabilization and flight control techniques to compensate for this uncertainty. In this research, an advanced nonlinear control algorithm, i.e. sliding mode control, was implemented. Flight experiments were carried out using an onboard flight control computer and various real-time autonomous attitude adjustments. The feasibility and robustness for flying in uncertain environments were also verified through real-time tests based on disturbances to the multi-rotor vehicle.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.706-711
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• 2008

This paper is presented an accurate localization scheme for mobile robots based on the fusion of ultrasonic satellite (U-SAT) with inertial navigation system (INS), i.e., sensor fusion. Our aim is to achieve enough accuracy less than 100 mm. The INS consist of a yaw gyro, two wheel-encoders. And the U-SAT consist of four transmitters, a receiver. Besides the localization method in this paper fuse these in an extended Kalman filter. The performance of the localization is verified by simulation and two actual data(straight, curve) gathered from about 0.5 m/s of driving actual driving data. localization methods used are general sensor fusion and sensor fusion through Kalman filter using data from INS. Through the simulation and actual data studies, the experiment show the effectiveness of the proposed method for autonomous mobile robots.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.