• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.70-76
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• 2020

Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.

• Journal of Industrial Technology
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• v.33 no.A
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• pp.55-60
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• 2013

In this paper, we proposed an efficient method for implementing a voice recognition elevator. Unlike the existing ones, the proposed system is based on the bluetooth communication and smartphones equipped with the google speech recognition software, which makes it possible that the speech recognition capability can be added to the previously installed elevators. In order to improve the recognition accuracy, instead of using the result of the google recognizer, we built a web server where the user data are accumulated and they are used for recognition error correction.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.601-607
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• 2012

The recognition of elevator door is needed for mobile service robots to moving between floors in the building. This paper proposed the sensor fusion approach using LRF (Laser Range Finder) and camera to solve the problem. Using the laser scans by the LRF, we extract line segments and detect candidates as the elevator door. Using the image by the camera, the door candidates are verified and selected as real door of the elevator. The outliers are filtered through the verification process. Then, the door state detection is performed by depth analysis within the door. The proposed method uses extrinsic calibration to fuse the LRF and the camera. It gives better results of elevator door recognition compared to the method using LRF only.

• Journal of the Speleological Society of Korea
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• no.88
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• pp.1-7
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• 2008

Recently, it is one of very interest technology of Human Computer Interaction(HCI). Nowadays, it is easy to find out that, for example, inside SF movies people has talking to computer. However, there are difference between CPU language and ours. So, we focus on connecting to CPU. For 30 years many scientists experienced in that technology. But it is really difficult. Our project goal is making that CPU could understand human voice. First of all the signal through a voice sensor will move to BCD (binary code). That elevator helps out people who wants to move up and down. This product's point is related with people's safety. Using a PWM for motor control by ATmega16, we choose a DC motor to drive it because of making a regular speed elevator. Furthermore, using a voice identification module the elevator driven by voice sensor could operate well up and down perfectly from 1st to 10th floor by PWM control with ATmega16. And, it will be clearly useful for high-rise vertical shift with voice recognition sensor driven.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.161-163
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• 2021

In an apartment or private building, it is difficult for the user to operate the elevator button in a similar situation with luggage in both hands. In an environment where human contact must be minimized due to a highly infectious virus such as COVID-19, it is inevitable to operate an elevator based on untact. This paper proposes an operating system capable of operating the elevator by using the user's voice and image processing through the user's face without pressing the elevator button. The elevator can be operated to a designated floor without pressing a button by detecting the face of a person entering the elevator by detecting the person's face from the camera installed in the elevator, matching the information registered in advance. When it is difficult to recognize a person's face, it is intended to enhance the convenience of elevator use in an untouched environment by controlling the floor of the elevator using the user's voice through a microphone and automatically recording access information.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.55-61
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• 2020

Getting on and off an elevator is one of the most important parts for multi-floor navigation of a mobile robot. In this study, we proposed the method for the pose recognition of elevator doors, safe path planning, and motion estimation of a robot using RGB-D sensors in order to safely get on and off the elevator. The accurate pose of the elevator doors is recognized using a particle filter algorithm. After the elevator door is open, the robot builds an occupancy grid map including the internal environments of the elevator to generate a safe path. The safe path prevents collision with obstacles in the elevator. While the robot gets on and off the elevator, the robot uses the optical flow algorithm of the floor image to detect the state that the robot cannot move due to an elevator door sill. The experimental results in various experiments show that the proposed method enables the robot to get on and off the elevator safely.

• Convergence Security Journal
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• v.23 no.2
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• pp.67-74
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• 2023

An elevator is a mechanical and electronic device composed of about 20,000 various parts, and is systematically operated with a close relationship with each other. By intuitively understanding this complex elevator structure and efficiently recognizing the operating model, it will be possible to increase the understanding of the elevator system and the efficiency of maintenance. The existing elevator management system is a process of collecting and understanding information based on data generated from elevators, and has a structure that lacks efficiency in expressing and managing real-world information during elevator maintenance. Therefore, this paper proposes a simulator framework that can operate efficiently based on the actual elevator model. By constructing the recognition of specific objects through a 3D-based service model and visualizing the operation process, it will be possible to enhance the understanding of the structure and operation required for elevator operation. To this end, the core components of the elevator system are identified, the relationship between them and the operating method are visualized, and a simulator is implemented. Based on this, it will be possible to provide a realistic information management and operating environment in virtual space and real platform.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.1-100
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• 2002

In this paper, we present autonomous mobile robot system, which has an image recognition module and perform tasks by itself with manipulator. Autonomous mobile robot can push each individual button on an elevator panel from a person's command. After the robot receives its command, it analyzes the image information of the elevator button that is acquired by CCD camera in an indoor environment with an elevator. In order to recognize the numbers on the button, the robot separates the number area in button and recognizes the segment through a neural network algorithm. We use the bar code form on the manipulator to find the position of the end of manipulator. The validity of the proposed method i...

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.4
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• pp.45-52
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• 2019

The most ordinary form of residential type in Korea is a plate-type apartment, and the common space in these apartment is attracting as an important factor for enhancing social exchanges among neighbors and forming community consciousness. In addition, it provides a sense of psychological security by enabling natural exchanges and communication in contemporary society. It is desirable to plan the flow of space in such a way that private, semi-private, semi-public, and public spaces are linked. Semi-private and semi-public spaces can be defined as common spaces. Semi-private spaces are strongly recognized in the order of unit household entrance, main entrance, elevator, corridor, staircase, playground, bench, trail, walkway and parking lot, exercise space, main/back gate, the ability to gratify is increased sense of belonging, ownership consciousness formation, defensive function. Semi-public space is strongly recognized in the order of playground, bench, exercise space, trail, main entrance, walkway and parking lot, unit household entrance, main/back gate, corridor, staircase, elevator, the ability to gratify is increase of social contact, Secondary activity space function. In addition, the function to gratify in the common space differs according to gender and age group among resident characteristics, and differs according to corridor type, parking lot type and main entrance type. Therefore, differentiated planning of common space is needed in consideration of these differences in the design of common space in future.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.859-864
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• 2017

IoT is a new emerging technology to lead the $4^{th}$ industry renovation and has been widely used in industry and home to increase the quality of human being. In this paper, IoT based face detection and recognition system for a smart elevator is developed. Haar cascade classifier is used in a face detection system and a proposed PCA algorithm written in Python in the face recognition system is implemented to reduce the execution time and calculates the eigenfaces. SVM or Euclidean metric is used to recognize the faces detected in the face detection system. The proposed system runs on RaspberryPi 3. 200 sample images in ORL face database are used for training and 200 samples for testing. The simulation results show that the recognition rate is over 93% for PP+EU and over 96% for PP+SVM. The execution times of the proposed PCA and the conventional PCA are 0.11sec and 1.1sec respectively, so the proposed PCA is much faster than the conventional one. The proposed system can be suitable for an elevator monitoring system, real time home security system, etc.