Earticle

최근에 개발된 시스템 온칩 프로세서는 통합 성능을 요구하는 작업의 가능성을 제공하였으며, 이러한 작업은 예전에는 우수한 성능을 가진 컴퓨터의 도움만으로 수행 할 수 있는 것이었다. 본 논 문에서는 실제 환경 하에서 자율 이동 장치의 GPS 위치측정을 개선하기 위해 임베디드 영상처리기 법을 활용하는 고급 제어 시스템을 소개한다. 메인 컨트롤 시스템은 Raspberry PI 개발 보드에 통합 된 ARM(SoC.) 아키텍처를 기반으로 한다. 제시한 제어 시스템은 실시간 비디오 캡처, 전력-효율적 이미지 처리 작 업, 예를 들어 (임계 값 처리, 이진화, 모션 감지 등) 및 비디오와 같은 스트리밍 결과 이미지를 처리 할 수 있다. GPS 정밀도는 WAAS(EGNOS) 위성을 활용하여 다만 3 미터의 정밀도를 제공 할 수 있다. 제안한 솔루션은 도로와 보도의 경계를 감지하기 위해 GPS 솔루션 및 임베디드 이 미지 처리를 사용한다. 일부 도로나 통로가 길가의 흰색 선을 제공하지 않기 때문에 제시한 알고리 즘은 길가의 흰색 선을 검출하지 않고 보편적인 도로나 보도를 감지한다. 제안한 시스템은 소형 이 동장치에 사용할 수 있다. 예를 들어, 생산 공간 사이의 긴 거리를 가진 중공업 산업 단지에서 부품 수송을 위한 이동장치 등에 사용할 수 있다.

A recent development in system-on-chip processors provides possibilities of integration performancedemanding tasks, which can be performed only with the help of superior range of computers before. The article introduces advanced control system with embedded image processing to improving GPS localization of autonomous mobile devices in real environment. The main control system is based on ARM (SoC.) architecture integrated in Raspberry PI development board. Presented control systems can handle real-time video capturing, power-efficient image processing operation for example (thresholding, binarization, motion detection, ...etc.) and streaming results images as video. GPS precision can provide only 3 meters precision together with WAAS (Egnos) satellite. Our solution uses GPS solution and embedded image processing to detect border of roads or sidewalks. Our algorithm detects road or sidewalk universally without detection of white line in roadside, because pathways and some roads cannot provide this feature. Control system can be used for small autonomous mobile devices for example parts transport in industrial park of heavy industries, where are long distances between production halls.

Fires are one of the most frequent natural disasters in the world. To minimize the damage from the fire, it is important to build surveillance systems for detecting fire with fire detection algorithms, and a variety of deep learning networks have been proposed with sufficiently high accuracy. However, regardless of the performance of the existing solutions, such systems are bound to a fixed environment so that its coverage is limited. Therefore, in this paper, we propose a fire detection system using mobile robots so as to overcome this limitation. Based on a freely moving robot driving system, the proposed system consist of IoT devices, edge cloud computing, and fire detection algorithm. We hope our proposed system offers useful insights to building practical mobile fire detection systems for minimizing the damages caused by fire.

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on indoor mobile robot position recognition and driving experiment using QR Code during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on the driving control of indoor mobile robot during the development of QR Code-aware indoor mobility robots.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses on experimental environments for testbeds during the development of QR Code-aware indoor mobility robots.

교육용으로 사용하는 인공 지능형 이동 로봇의 플랫폼을 개발하였다. 이 로봇은 주제어기, 모터드라이버부, 바퀴부, 센서부, 통신부 등으로 구성되고, 모듈화되어 있으며, 무선 통신을 사용하여 PC와 연결하여 사용할 수 있다. 카메라를 부착하여 환경 영상을 PC로 전송할 수 있으며, PC를 통하여 음성 인식에 의한 구동이 가능하도록 하여 인공 지능형 이동이 가능하도록 하였다. 초음파 센서, 광센서를 이용하여 장애물 회피 주행도 가능하도록 하였다. 이와 같은 기능을 가진 교육용 로봇은, 학생들의 문제 해결력, 창의력, 협동하는 능력, 논리적 사고, 컴퓨터 프로그래밍 등의 능력 배양을 뒷받침할 수 있는 교육용 기자재로서 활용성이 매우 클 것이다.

Intelligent mobile robot platform was developed for education. It is composed of main controller, motor driver, wheel, sensor, and data communication part. It is modularized and connected to personal computer by wireless communication. Environmental image can be transmitted to personal computer and the robot can be driven by the command made by voice recognition through the personal computer. Obstacle avoidance navigation is possible using sonar and light sensor. This robot can be used for various kinds of intelligent robot technology education

본 논문에서는 감염병 환자를 격리하여 치료가 이루어지는 생활치료센터, 음압격리병동에서 의료진의 업무를 보조할 수 있 는 IT 및 로봇 기술이 적용된 시스템을 제안한다. 로봇과 같은 첨단기기가 적용되기 위해 기존의 격리시설에서 이루어지는 의료 진의 업무 프로세스를 먼저 파악하였으며, 각 업무마다 의료진이 느낄 수 있는 고충점(Pain Point)들을 찾아내었다. 이를 통해 본 연구에서는 격리치료시설에 의료진과 환자의 소통을 위한 스마트 기기 기반의 메시지 센터, 음압병실에서의 의료진과의 연 결을 담당하는 병실 로봇, 그리고 격리시설의 물류 배송 및 수거를 담당하는 물류 로봇을 제안한다. 격리치료시설 업무프로세 스에서 파악된 고충점을 해결 할 수 있는 방안을 각 첨단 기기들을 활용해 서비스화하여 격리치료 시설 보조용 시스템 서비스를 구성하였다.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a study on the speculative navigation using auxiliary encoder during the development of QR Code-aware indoor mobility robots.

The role of QR code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR codes and the convenience of producing and attaching a lot of information within QR codes have been raised, and many of these reasons have made QR codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR codes with the same horizontal and vertical sides, and the error is to create a QR code robot with accuracy to reach within 3mm. This paper focuses on the driving operation techniques during the development of QR code-aware indoor mobility robots.

The role of QR code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR codes and the convenience of producing and attaching a lot of information within QR codes have been raised, and many of these reasons have made QR codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR codes with the same horizontal and vertical sides, and the error is to create a QR code robot with accuracy to reach within 3mm. This paper focuses on the moving control model during the development of QR code-aware indoor mobility robots.

Path planning is necessary for mobile robots to perform precise and rapid tasks. A collision avoidance function must be included so that the robot can move safely during work, and it must be able to create an optimal path to reduce work execution time and save energy. In this paper, we propose a smart route generation algorithm that searches for global route with an algorithm that can speed up route search and integrates the TEB algorithm that can search for regional optimum routes in real time according to the situation. The performance of the proposed algorithm was verified through actual driving experiments of mobile robots.

With the recent development of autonomous driving technology, many researchers have studied autonomous mobile robots. Accordingly, they are developing diverse mobile robot actuators. However, most actuators mainly use reducers made of chains, belts, multi-stage gears, etc. So the volume and size of the actuators increase, and power transmission efficiency tends to be relatively low. Therefore, this study has proposed the reducer of the mobile robot actuator using a complex planetary gear train with small volume and high power transmission efficiency, and has confirmed the stability of the proposed reducer through finite element analysis.

The role of QR Code robots in smart logistics is great. Cognitive robots, such as logistics robots, were mostly used to adjust routes and search for peripheral sensors, cameras, and recognition signs attached to walls. However, recently, the ease of making QR Codes and the convenience of producing and attaching a lot of information within QR Codes have been raised, and many of these reasons have made QR Codes recognizable as visions and others. In addition, there have been cases in developed countries and Korea that control several of these robots at the same time and operate logistics factories smartly. This representative case is the KIVA robot in Amazon. KIVA robots are only operated inside Amazon, but information about them is not exposed to the outside world, so a variety of similar robots are developed and operated in several places around the world. They are applied in various fields such as education, medical, silver, military, parking, construction, marine, and agriculture, creating a variety of application robots. In this work, we are developing a robot that can recognize its current position, move and control in the directed direction through two-dimensional QR Codes with the same horizontal and vertical sides, and the error is to create a QR Code robot with accuracy to reach within 3mm. This paper focuses a suggestion of control method in QR Code-aware indoor mobility robots.

Robots for a wide range of purposes have been developed along with the rapid industrialization. On the basis of higher convenience, the robots have been creating new industrial environment. The robots are generally classified into service robots and industrial robots. Robots in various shapes have been developed on the basis of the autonomous mobile robots. The autonomous mobile robots have the possibility to crash against any object in their moving range. This paper suggests a collision avoidance method to prevent collision of robots. The collision avoidance method analyzes the road context data and makes a robot move to a safe area. The collision avoidance method proposed in this paper converts the road context data into the information value. The collision avoidance method analyzes the present risk on the basis of the converted information value. The collision avoidance method makes a robot move to a safe area when crash is estimated by the information analysis.