• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.345-354
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• 2014

In this paper, we propose a real-time algorithm for estimating the relative position and velocity of a person with respect to a robot using a Kinect sensor and an extended Kalman filter (EKF). Additionally, we propose an algorithm for controlling the robot in the proximity of a person in a variety of modes. The algorithm detects the head and shoulder regions of the person using a histogram of oriented gradients (HOG) and a support vector machine (SVM). The EKF algorithm estimates the relative positions and velocities of the person with respect to the robot using data acquired by a Kinect sensor. We tested the various modes of proximity movement for a human in indoor situations. The accuracy of the algorithm was verified using a motion capture system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.327-332
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• 2017

As Internet of Things (IoT) technology advances, there is a growing demand for location-based services (LBSs) to identify users' mobility and identity. The initial LBS system was mainly used to measure position information by measuring the phase of a signal transmitted from a global positioning system (GPS) satellite or by measuring distance to a satellite by tracking the code of a carrier signal. However, the use of GPS satellites is ineffective, because it is difficult to receive satellite signals indoors. Therefore, research on wireless communications systems like ultra-wide band (UWB), radio frequency identification (RFID), and ZigBee are being actively pursued for location recognition technology that can be utilized in an indoor environment. In this paper, we propose an LBS system that includes the 2.45GHz band for chirp spread spectrum (CSS), and the 3.1-10.6GHz band and the 250-750MHz bands for UWB using the IEEE 802.15.4a standard for low power-based location recognition. As a result, we confirmed that the 2.45GHz Industrial, Scientific and Medical (ISM) band RF transceiver and the ranging function can be realized in the hardware and has 0dBm output power.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.56-60
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• 2014

Highly concentrated sunlight obtained from a solar concentrator mounted on a solar tracker can be divided into the infrared and visible region before it is actually applied. That is, solar rays are directed toward a unit optically separating sunlight into the infrared and visible region by a hot mirror as they impinge on the surface of a secondary reflector. The Infrared rays can be utilized for thermoacoustic applications while visible rays can be utilized for indoor lighting. This work introduces the separation of two different kinds of light; sunlight and artificial light. As for the artificial light, its wavelength extended from 400m to 720m for the visible region and 620m to 940m for the infrared region. Comparatively, a series of tests performed on sunlight revealed its separation in the visible region from 460m to 680m whereas from 620m to 940m for the artificial light.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.5
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• pp.488-495
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• 2012

The real-time indoor location technology using radio waves has been studied in a variety of environments. One of them, a ship which consists of steel structure has high reception rate but causes significant ranging error due to the reflection of radio waves. In order to reduce location measurement errors that occurs in such a environment, this paper, based on CSS of IEEE 802.15.4a, presents compensation algorithm for localization using modified bilateration and pyroelectric sensor in a ship. The proposed system reduces the number of fixed nodes by estimating the appropriate reception distance between mobile node and fixed node through the analysis of CSS characteristic in a narrow passage such as ship corridors. Also, in the corner section which the ranging errors are significantly fluctuated due to the reflection and diffraction of radio waves, we recognize the location by tracking the a moving section using modified bilateration technique and pyroelectric sensor. The experimental results show that the location accuracy and efficiency of the proposed algorithm are improved 86.2 % compared to general method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.10
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• pp.3873-3879
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• 2010

Home service robot are not working in the fixed task such as industrial robot, because they are together with human in the same indoor space, but have to do in much more flexible and various environments. Most of them are developed on the base of the wheel-base mobile robot in the same method as a vehicle robot for factory automation. In these days, for holonomic system characteristics, omni-directional wheels are used in the mobile robot. A holonomicrobot, using omni-directional wheels, is capable of driving in any direction. But trajectory control for omni-directional mobile robot is not easy. Especially, azimuth control which sensor uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A trajectory controller for an omni-directional mobile robot, which each motor is controlled by an individual PID law to follow the speed command from inverse kinematics, needs a precise sensing data of its azimuth and exact estimation of reference azimuth value. It has imprecision and uncertainty inherent to perception sensors for azimuth. In this paper, they are solved by using fuzzy logic inference which can be used straightforward to perform the control of the mobile robot by means of the fuzzy behavior-based scheme already existent in literature. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.721-730
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• 2012

In this paper the problem of a moving control of an automatic guided vehicle(AGV) which transports a dead body to a designated cinerator safely in a crematorium, an special indoor environment, will be discussed. Since a method of burying guided lines in the floor is not proper to such an environment, a method of moving control of an AGV based on infrared ray sensors is now proposed. With this approach, the AGV emits infrared ray to the landmarks adheres to the ceiling to find a moving direction and then moves that direction by recognizing them. One of the typical problems for this method is that dead zone and/or overlapping zone may exist when the landmarks are deployed. To resolve this problem, an algorithm of recognizing double landmarks at each time is applied to minimize occurrences of sensing error. In addition, at the turning area to entering the designated cinerator, to fit an AGV with the entrance of the designated cinerator, an algorithm of controlling the velocity of both the inner and outer wheel of it. The functional correctness of our proposed algorithm has been verified by using a prototype vehicle. Our real AGV system has been applied to a crematorium and it moves automatically within an allowable range of location error.