• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1771-1774
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• 2005

Recently, RFID has become popular in the field of remote sensing applications. Location awareness is one of the most important keys to deploying RFID for advanced object tracking. Generally, multiple reference RF stations or additional sensors are used for the location sensing with RFID, but, particularly in indoor environments, spatial layout and cost problems limit the applicability of those approaches. In this paper, we propose a novel method for location sensing with active RFID systems not requiring the need for reference stations or additional sensors. The system triangulates the position of RF signal source using the signal pattern of the loop antenna connected to the power detector. The power detector consists of a signal strength detector and a signal analysis unit. The signal analysis unit indicates the signal strength and serial number using the signal from the strength detector, and provides the direction of the signal to the application target. We designed three different signal analysis units depending on the threshold type. The developed system can sense the direction to the transponder located over 10 m away within the maximum error of $5^{\circ}$. It falls within a reasonable range in our normal office environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.161-166
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• 2006

Localization of mobile agent within a sensing network is a fundamental requirement for many applications, using networked navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, This paper describes a networked sensor-based navigation method in an indoor environment for an autonomous mobile robot which can navigate and avoid obstacle. In this method, the self-localization of the robot is done with a model-based vision system using networked sensors, and nonstop navigation is realized by a Kalman filter-based STSF(Space and Time Sensor Fusion) method. Stationary obstacles and moving obstacles are avoided with networked sensor data such as CCD camera and sonar ring. We will report on experiments in a hallway using the Pioneer-DX robot. In addition to that, the localization has inevitable uncertainties in the features and in the robot position estimation. Kalman filter scheme is used for the estimation of the mobile robot localization. And Extensive experiments with a robot and a sensor network confirm the validity of the approach.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.314-319
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• 2009

In this paper, the network performance of a turbo coded optical code division multiple access (COMA) system with cross-layer, which is between physical and network layers, concept is analyzed and simulated We consider physical and MAC layers in a cross-layer concept. An intensity-modulated/direct-detection (IM/DD) optical system employing pulse position modulation (PPM) is considered In order to increase the system performance, turbo codes composed of parallel concatenated convolutional codes (PCCCs) is utilized. The network performance is evaluated in terms of bit error probability (BEP). From the simulation results, it is demonstrated that turbo coding offers considerable coding gain with reasonable encoding and decoding complexity. Also, it is confirmed that the performance of such an optical COMA network can be substantially improved by increasing the interleaver length and the number of iterations in the decoding process. The results of this paper can be applied to implement the indoor optical wireless LANs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.586-589
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• 2015

A computer presentation system by using hand-motion identification rules is proposed. To identify hand motions of a presenter, a face region is extracted first using haar classifier. A motion status(patterns) and position of hands is discriminated using the center of gravities of user's face and hand after segmenting the hand area on the YCbCr color model. User's hand is applied to the motion detection rules and then presentation control command is then executed. The proposed system utilizes the motion identification rules without the use of additional equipment and it is then capable of controlling the presentation and does not depend on the complexity of the background. The proposed algorithm confirmed the stable control operation via the presentation of the experiment in the dark illumination range of indoor atmosphere (lx) 15-20-30.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.1
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• pp.30-38
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• 2014

The purpose of this study is to build and manage environment models with line segments from sonar range data on obstacles in unknown and varied environments. The proposed method therefore employs a two-stage data-transform process in order to extract environmental line segments from range data on obstacles. In the first stage, the occupancy grid extracted from the range data is accumulated to form a two-dimensional local histogram grid. In the second stage, a line histogram extracted from a local histogram grid is based on a Hough transform, and matching serves as a means of comparing each of the segments on a global line segments map against the line segments to detect the degree of similarity in the overlap, orientation, and arrangement. Each of these tests is formulated by comparing one of the parameters in the segment representation. After the tests, new line segments can be found at maximum-density cells in the line histogram, and they are composed onto the global line segment map. The proposed technique is demonstrated in experiments in an indoor environment.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.213-221
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• 2017

Utilizing the existing polishing robot prevents unrestricted change of direction, driving, and identification of driving pathway. To overcome this barrier, driving mechaism has been designed with Omniwheels with encoders and RSSI method of beacon system has been utilized to identify the driving path by position recognition. Due to the wheel characteristics, the Omniwheel mobile robot generates greater slip than the conventional mobile robot, which reduces its driving accuracy. Therefore, to improve the driving accuracy, the localization is conducted through the fusion of encoder and RSSI of beacon data to compensate for the errors caused by Dead Reckoning and inaccuracy of sensors. Finally, the localization accuracies of the proposed and conventional indoor localization method are compared to show effectiveness of the proposed driving control for a polishing robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5422-5441
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• 2016

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.

• Journal of Power System Engineering
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• v.17 no.5
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• pp.112-120
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• 2013

In this study, we propose an improved view-based navigation method for obstacle avoidance and evaluate the effectiveness of the method in real environments with real obstacles. The proposed method possesses the ability to estimate the position and rotation of a mobile robot, even if the mobile robot strays from a recording path for the purpose of avoiding obstacles. In order to achieve this, ego-motion estimation was incorporated into the existing view-based navigation system. The ego-motion is calculated from SURF points between a current view and a recorded view using a Kinect sensor. In conventional view-based navigation systems, it is difficult to generate alternate paths to avoid obstacles. The proposed method is anticipated to allow a mobile robot greater flexibility in path planning to avoid humans and objects expected in real environments. Based on experiments performed in an indoor environment using a mobile robot, we evaluated the measurement accuracy of the proposed method, and confirmed its feasibility for robot navigation in museums and shopping mall.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.242-247
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• 2008

As an absolute positioning system, iGS is designed based on ultrasonic signals whose speed can be formulated clearly in terms of time and room temperature, which is utilized for a mobile robot localization. The iGS is composed of an RFID receiver and an ultra-sonic transmitter, where an RFID is designated to synchronize the transmitter and receiver of the ultrasonic signal. The traveling time of the ultrasonic signal has been used to calculate the distance between the iGS system and a beacon which is located at a pre-determined location. This paper suggests an effective operation method of iGS to estimate position of the mobile robot working in unstructured environment. To expand recognition range and to improve accuracy of the system, two strategies are proposed: utilization of beacons belonging to neighboring blocks and removal of the environment-reflected ultrasonic signals. As the results, the ubiquitous localization system based on iGS as a pseudo-satellite system has been developed successfully with a low cost, a high update rate, and relatively high precision.