• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2461-2466
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• 2003

This paper presents a simple sensor fusion algorithm using neural network for navigation of mobile robots with obstacle avoidance and trap recovery. The multiple sensors input sensor data to the input layer of neural network activating the input nodes. The multiple sensors used include optical encoders, ultrasonic sensors, infrared sensors, a magnetic compass sensor, and GPS sensors. The proposed sensor fusion algorithm is combined with the VFH(Vector Field Histogram) algorithm for obstacle avoidance and AGPM(Adaptive Goal Perturbation Method) which sets adaptive virtual goals to escape trap situations. The experiment results show that the proposed low-level fusion algorithm is effective for real-time navigation of mobile robot.

• Solar Energy
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• v.15 no.3
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• pp.53-58
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• 1995

The objectives of this study are to introduce the energy simulation program BLDSYM, to verify the approach, and to demonstrate the energy saving opportunities. A case study model for Hoover Middle School, OK, USA has been introduced as a base case simulation. Air-side variable air volume(VAV) and water-side variable flow hydronic(VFH) system have been recommended, modeled and simulated to quantify the energy savings compared with the base system, which is typically constant air and water flow system. More than 30% of energy savings could be obtained with the optimum variable flow system.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1995.05a
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• pp.88-93
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• 1995

The purpose of this study is to introduce the energy simulation program BLDSYM, verify the approach. and demonstrate the energy saving opportunities. A case study model for Hoover Middle School, OK USA has been introduced as a base case simulation. Air-side variable air volume (VAV) and water-side variable flow hydronic (VFH) system have been recommended, modeled and simulated to quantify the energy savings compared with the base system, which is typically constant air and water flow system. More than 30 % of energy savings could be obtained with the optimum variable flow system.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.12
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• pp.75-82
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• 2010

This paper presents a wideband ${\Delta}{\Sigma}$ fractional-N frequency synthesizer for a multi-band single chip CMOS RFIC transceivers. A wideband VCO utilizes a 6-bit switched capacitor array bank for 2340~3940 MHz frequency range. VCO frequency calibration circuit is designed for optimal capacitor bank code selection before phase locking process. It finishes the calibration process in $2{\mu}s$ over the whole frequency band. The LO generation block has selectable multiple division ratios of ${\div}2$, ${\div}16$, and ${\div}32$ to generate LO I/Q signals for T-DMB/DAB/FM Radio systems in L-Band (1173~1973 MHz), VHF-III (147~246 MHz), VFH-II (74~123 MHz), respectively. The measured integrated phase noise is quite low as it is lower than 0.8 degree RMS over the whole frequency band. Total locking time of the ${\Delta}{\Sigma}$ frequency synthesizer including VCO frequency calibration time is less than $50{\mu}s$. The wideband ${\Delta}{\Sigma}$ fractional-N frequency synthesizer is fabricated in $0.13{\mu}m$ CMOS technology, and it consumes 15.8 mA from 1.2 V DC supply.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.377-388
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• 2020

In this paper, the autonomous mobile robot whit only LRF sensors proposes an algorithm for avoiding moving obstacles in an environment where a global map containing fixed obstacles. First of all, in oder to avoid moving obstacles, moving obstacles are extracted using LRF distance sensor data and a global map. An ellipse-shaped safety radius is created using the sum of relative vector components between the extracted moving obstacles and of the autonomuos mobile robot. Considering the created safety radius, the autonomous mobile robot can avoid moving obstacles and reach the destination. To verify the proposed algorithm, use quantitative analysis methods to compare and analyze with existing algorithms. The analysis method compares the length and run time of the proposed algorithm with the length of the path of the existing algorithm based on the absence of a moving obstacle. The proposed algorithm can be avoided by taking into account the relative speed and direction of the moving obstacle, so both the route and the driving time show higher performance than the existing algorithm.