• 제어로봇시스템학회논문지
• /
• 제20권2호
• /
• pp.218-222
• /
• 2014

In this paper, we introduce an autonomous calibration method for a 2D laser displacement sensor (e.g. laser vision sensor and laser range finder) by matching a single point on a flat structure. Many arc welding robots install a 2D laser displacement sensor to expand their application by recognizing their environment (e.g. base metal and seam). In such systems, sensing data should be transformed to the robot's coordinates, and the geometric relation (i.e. rotation and translation) between the robot's coordinates and sensor coordinates should be known for the transformation. Calibration means the inference process of geometric relation between the sensor and robot. Generally, the matching of more than 3 points is required to infer the geometric relation. However, we introduce a novel method to calibrate using only 1 point matching and use a specific flat structure (i.e. circular hole) which enables us to find the geometric relation with a single point matching. We make the rotation component of the calibration results as a constant to use only a single point by moving a robot to a specific pose. The flat structure can be installed easily in a manufacturing site, because the structure does not have a volume (i.e. almost 2D structure). The calibration process is fully autonomous and does not need any manual operation. A robot which installed the sensor moves to the specific pose by sensing features of the circular hole such as length of chord and center position of the chord. We show the precision of the proposed method by performing repetitive experiments in various situations. Furthermore, we applied the result of the proposed method to sensor based seam tracking with a robot, and report the difference of the robot's TCP (Tool Center Point) trajectory. This experiment shows that the proposed method ensures precision.

• International Journal of Control, Automation, and Systems
• /
• 제2권2호
• /
• pp.201-206
• /
• 2004

Counters for the various kinds of banknotes require high-speed distinctive point extraction and recognition. In this paper we propose a new point extraction and recognition algorithm for Euro banknotes. For distinctive point extraction we use a coordinate data extraction method from specific parts of a banknote representing the same color. To recognize banknotes, we trained 5 neural networks. One is used for inserting direction and the others are used for face value. The algorithm is designed to minimize recognition time by using a minimal amount of recognition data. The simulated results show a high recognition rate and a low training period. The proposed method can be applied to high speed banknote counting machines.

• Journal of Animal Science and Technology
• /
• 제66권4호
• /
• pp.781-791
• /
• 2024

Bovine viral diarrhea (BVD) is a single-stranded, positive-sense ribonucleic acid (RNA) virus belonging to the genus Pestivirus of the Flaviviridae family. BVD frequently causes economic losses to farmers. Among bovine viral diarrhea virus (BVDV) strains, BVDV-1b is predominant and widespread in Hanwoo calves. Reverse-transcription polymerase chain reaction (RT-PCR) is an essential method for diagnosing BVDV-1b and has become the gold standard for diagnosis in the Republic of Korea. However, this diagnostic method is time-consuming and requires expensive equipment. Therefore, Clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) systems have been used for point-of-care (POC) testing of viruses. Developing a sensitive and specific method for POC testing of BVDV-1b would be advantageous for controlling the spread of infection. Thus, this study aimed to develop a novel nucleic acid detection method using the CRISPR-Cas13 system for POC testing of BVDV-1b. The sequence of the BVD virus was extracted from National Center for Biotechnology Information (NC_001461.1), and the 5' untranslated region, commonly used for detection, was selected. CRISPR RNA (crRNA) was designed using the Cas13 design program and optimized for the expression and purification of the LwCas13a protein. Madin Darby bovine kidney (MDBK) cells were infected with BVDV-1b, incubated, and the viral RNA was extracted. To enable POC viral detection, the compatibility of the CRISPR-Cas13 system was verified with a paper-based strip through collateral cleavage activity. Finally, a colorimetric assay was used to evaluate the detection of BVDV-1b by combining the previously obtained crRNA and Cas13a protein on a paper strip. In conclusion, the CRISPR-Cas13 system is highly sensitive, specific, and capable of nucleic acid detection, making it an optimal system for the early point-of-care testing of BVDV-1b.

• The Journal of Korean Physical Therapy
• /
• 제14권1호
• /
• pp.159-167
• /
• 2002

The Halliwick concept was developed by James McMillan over 50 years ago, and began as a method for teaching swimming to children with physical disables. After that the Halliwcik concept was developed as a specific strategy(called the Ten-Point Program) for teaching swimming to children with disabilities. Soon after the changes in the physical and emotional behavior were attributed to a unique teaching/learning philosophy and a psycho-sensory-motor learning program that is enhanced by hydrodynamics. Recognizing the therapeutic effects of the Ten-Pont Program adapted the program as a therapeutic intervention called Water Specific Therapy or the Logic Approach to Therapy in Water.

• 대한전자공학회논문지SP
• /
• 제48권2호
• /
• pp.96-101
• /
• 2011

소실점이란 실제 공간의 평행한 선들이 영상 내에 투영되면서 한곳에 모이는 점이다. 본 논문에서는 이러한 소실점의 특성을 이용한 실시간 소실점 검출 알고리즘을 제안한다. 기존의 소실점 검출 방법은 1) 복잡한 계산이 요구되거나 2) 알고리즘에 따라 소실점을 검출할 수 있는 영상이 제한되어 있다. 제안하는 방법은 블록 기반의 HOG(Histogram of Oriented Gradient)를 구하여 영상의 구조적 특성을 이용하는 것으로 영상 내에 존재하는 소실점을 실시간으로 검출한다. 먼저 영상의 블록 단위로 HOG 기술자를 구한 뒤, 제안하는 동적 프로그래밍(dynamic programing)을 이용하여 소실점의 위치를 예측한다. 본 논문에서는 다양한 영상에 대한 실험을 통해 제안하는 알고리즘이 효율적인 소실점 검출 방법임을 보이고자 한다.

• 드라이브 ㆍ 컨트롤
• /
• 제21권2호
• /
• pp.65-71
• /
• 2024

In this study, we suggested a key-point detection method for robot harvesting of oriental melon. Our suggested method could be used to detect the detachment part and major composition of oriental melon. We defined four points (harvesting point, calyx, center, bottom) based on tomato with characteristics similar to those of oriental melon. The evaluation of estimated key-points was conducted by pixel error and PDK (percentage of detected key-point) index. Results showed that the average pixel error was 18.26 ± 16.62 for the x coordinate and 17.74 ± 18.07 for the y coordinate. Considering the resolution of raw images, these pixel errors were not expected to have a serious impact. The PDK score was found to be 89.5% PDK@0.5 on average. It was possible to estimate oriental melon specific key-point. As a result of this research, we believe that the proposed method can contribute to the application of harvesting robot system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권9호
• /
• pp.2976-2990
• /
• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.

• International Journal of Aeronautical and Space Sciences
• /
• 제16권1호
• /
• pp.64-76
• /
• 2015

This paper suggests applying pseudospectral model predictive method for exo-atmospheric guidance. The method is a fusion of pseudospectral law and model predictive control, in which a two point boundary value problem is formulated using model predictive approach and solved by applying pseudospectral law. In this work, the method is applied to exo-atmospheric guidance with specific target requirement. The existing exo-atmospheric guidance methods suffice general requirements for guidance, but cannot ensure specific target constraints; whereas, the presented method is able to do so. The proposed guidance law is assessed through simulation of perturbed cases, and the tests suggest that the method is able to operate semi-autonomously under control and thrust vector perturbations.

• 한국군사과학기술학회지
• /
• 제2권2호
• /
• pp.30-39
• /
• 1999

In this paper, we have proposed a novel method which can compose a reflected signal of the underwater target. The synthesis of the reflected signal in the target, the synthesized signal being similar to the characteristics of the reflected signal in the real target, is used the highlight model at the specific points of the target. We suggest the synthesis method of the reflected signal of the target using the pulsewidth variation and each other doppler effect at the highlight point, and compare the composed signal by the proposed method with that by conventional one. Simulation results show that the composed signal using the proposed method and the reflected signal of the real target is similar to the spectral characteristics.

• 제어로봇시스템학회논문지
• /
• 제19권4호
• /
• pp.290-298
• /
• 2013

Geomagnetic is refracted by building's wall and pillar. Therefore refracted geomagnetic is able to be used as feature point. In a specific space, a mobile device that is equipped with magnetic sensor array measures 3-axis magnetic field for each point. Magnetic field map is acquired by collecting the every sample point in the magnetic field. The measured magnetic field must be calibrated, because each magnetic sensor has a distortion. For this reason, sensor distortion model and sensor calibration method are proposed in this paper. Magnetic field that is measured by mobile device matches magnetic field map. Result of the matching is used for position estimation. This paper implements hardware system for position estimation method using magnetic field map.