• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.320-327
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• 2023

In this study, an FPGA-based sealer inspection system was developed to inspect the sealer applied to install vehicle glass on a car body. The sealer is a liquid or paste-like material that promotes adhesion such as sealing and waterproofing for mounting and assembling vehicle parts to a car body. The system installed in the existing vehicle design parts line does not detect the sealer in the glass rotation section and takes a long time to process. This study developed a line laser camera sensor and an FPGA vision signal processing module to solve this problem. The line laser camera sensor was developed such that the resolution and speed of the camera for data acquisition could be modified according to the irradiation angle of the laser. Furthermore, it was developed considering the mountability of the entire system to prevent interference with the sealer ejection machine. In addition, a vision signal processing module was developed using the Zynq-7020 FPGA chip to improve the processing speed of the algorithm that converted the profile to the sealer shape image acquired from a 2D camera and calculated the width and height of the sealer using the converted profile. The performance of the developed sealer application inspection system was verified by establishing an experimental environment identical to that of an actual automobile production line. The experimental results confirmed the performance of the sealer application inspection at a level that satisfied the requirements of automotive field standards.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.2
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• pp.223-229
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• 2024

Laser-induced plasmonic sintering of metal nanoparticles (NPs) holds significant promise as a technology for producing flexible conducting electrodes. This method offers immediate, straightforward, and scalable manufacturing approaches, eliminating the need for expensive facilities and intricate processes. Nevertheless, the metal NPs come at a high cost due to the intricate synthesis procedures required to ensure long-term reliability in terms of chemical stability and the prevention of NP aggregation. Herein, we induced the self-generation of metal nanoparticles from Ag organometallic ink, and fabricated highly conductive electrodes on flexible substrates through laser-assisted plasmonic annealing. To demonstrate the practicality of the fabricated flexible electrode, it was configured in a mesh pattern, realizing multi-touchable flexible touch screen panel.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.186-193
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• 2008

We propose a novel real-time obstacle avoidance method for rescue robots. This method, named the ELA(Emergency Level Around), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward safe position. In the ELA, we consider two sensor modules, PSD(Position Sensitive Detector) infrared sensors taking charge of obstacle detection in short distance and LMS(Laser Measurement System) in long distance respectively. Hence if a robot recognizes an obstacle ahead by PSD infrared sensors first, and judges impossibility to overcome the obstacle based on driving mode decision process, the order of priority is transferred to LMS which collects data of radial distance centered on the robot to avoid the confronted obstacle. After gathering radial information, the ELA algorithm estimates emergency level around a robot and generates a polar histogram based on the emergency level to judge where the optimal free space is. Finally, steering angle is determined to guarantee rotation to randomly direction as well as robot width for safe avoidance. Simulation results from wandering in closed local area which includes various obstacles and different conditions demonstrate the power of the ELA.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.579-585
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• 2008

Recently, many researches on autonomous mobile system have been proposed, which are possible to recognize its surrounding environment and navigate to destination without supervisor's intervention. Various sensors are mounted on the autonomous systems in order for the systems to move to destination safely without any accident. In this paper, we design an ontology-based autonomous system mounted laser distance sensors and cameras, and propose a method to conceptualize sensing information. We show the validity of the proposed method through the experiments of the system's navigation.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.2
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• pp.159-171
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• 2012

Aerosol direct radiative forcing (ADRF) retrieval method was developed by combining data from passive and active satellite sensors. Aerosol optical thickness (AOT) retrieved form the Moderate Resolution Imaging Spectroradiometer (MODIS) as a passive visible sensor and aerosol vertical profile from to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) as an active laser sensor were investigated an application possibility. Especially, space-born Light Detection and Ranging (Lidar) observation provides a specific knowledge of the optical properties of atmospheric aerosols with spatial, temporal, vertical, and spectral resolutions. On the basis of extensive radiative transfer modeling, it is demonstrated that the use of the aerosol vertical profiles is sensitive to the estimation of ADRF. Throughout the investigation of relationship between aerosol height and ADRF, mean change rates of ADRF per increasing of 1 km aerosol height are smaller at surface than top-of-atmosphere (TOA). As a case study, satellite data for the Asian dust day of March 31, 2007 were used to estimate ADRF. Resulting ADRF values were compared with those retrieved independently from MODIS only data. The absolute difference values are 1.27% at surface level and 4.73% at top of atmosphere (TOA).

• Journal of Welding and Joining
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• v.18 no.4
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• pp.70-75
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• 2000

The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal butt-joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor were determined for the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 mm, and it was revealed that the system has excellent seam tracking ability for the butt-joint of sheet metal.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.968-974
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• 2006

We are moving into the era of ubiquitous computing. Ubiquitous Sensor Network (USN) is a base of such computing paradigm, where recognizing the identification and the position of objects is important. For the object identification, RFID tags are commonly used. For the object positioning, use of sensors such as laser and ultrasonic scanners is popular. Recently, there have been a few attempts to apply RFID technology in robot localization by replacing the sensors with RFID readers to achieve simpler and unified USN settings. However, RFID does not provide enough sensing accuracy for some USN applications such as robot navigation, mainly because of its inaccuracy in distance measurements. In this paper, we describe our approach on achieving accurate navigation using RFID. We solely rely on RFID mechanism for the localization by providing coordinate information through RFID tag installed floors. With the accurate positional information stored in the RFID tag, we complement coordinate errors accumulated during the wheel based robot navigation. We especially focus on how to distribute RFID tags (tag pattern) and how many to place (tag granularity) on the RFID tag-floor. To determine efficient tag granularities and tag patterns, we developed a simulation program. We define the error in navigation and use it to compare the effectiveness of the navigation. We analyze the simulation results to determine the efficient granularities and tag arrangement patterns that can improve the effectiveness of RFID navigation in general.

• Korean Journal of Optics and Photonics
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• v.6 no.4
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• pp.365-372
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• 1995

A signal processing technique for interferometric fiber-optic sensors is proposed. It does not require a any special optic components such as phase modulator, $3times3$ couplers,to obtain the full sensitivity of the interferometer. Instead, it requires a reference interferometer for phase referencing and a reference mirror for intensity referencing, but intensity referencing can be done without using the r reference mirror. The new technique utilizes the frequency chirping of the laser diode to process t the sensor signal with both wide dynamic range and high sensitivity of the interferometer. It was a applied to an internal-mirrored FP interferometric temperature sensor to obtain the system noise of $4\times10^{-3\circ}C$ from I cm FP Interferometor sensor device.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.