• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1759-1764
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• 2005

Human Adaptive Mechatronics(HAM) is a new concept which was proposed in our university's research project sponsored by Japanese Ministry of Education, Sports, Culture, Science and Technology(MEXT), and is defined as "intelligent mechanical systems that adapt themselves to the user's skill under various environments, assist to improve the user's skill, and assist the human-machine system to achieve best performance". In this paper, the concept and key-items of HAM are mentioned. And the control strategy to realize a HAM human-machine system is explained in the case of physical-interface system, i.e. haptic system. The proposed assist-control of a force-feedback type haptic system includes online estimation of a operator's control characteristics, and a `force assist' function implemented as a change in the support ratio according to the identified skill level. We developed a HAM-haptic device test system, executed evaluation experiments with this apparatus, and analyzed the measured data. It was confirmed that the operator's skill could be estimated and that operator's performance was enhanced by the assist-control.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.777-782
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• 2007

Human Robot Interaction(HRI) through a haptic interface plays an important role in controlling robot systems remotely. The augmented usage of bio-signals in the haptic interface is an emerging research area. To consider operator's state in HRI, we used bio-signals such as ECG and blood pressure in our proposed force reflection interface. The variation of operator's state is checked from the information processing of bio-signals. The statistical standard variation in the R-R intervals and blood pressure were used to adaptively adjust force reflection which is generated from environmental condition. To change the pattern of force reflection according to the state of the human operator is our main idea. A set of experiments show the promising results on our concepts of human adaptive interface.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.10
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• pp.857-863
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• 2015

The need for human body posture robots has led researchers to develop dexterous design of exoskeleton robots. Quantitative techniques to assess human motor function and generate commands for robots were required to be developed. In this paper, we present a passivity based adaptive control algorithm for upper limb assist exoskeleton. The proposed algorithm can adapt to different subject parameters and provide efficient response against the biomechanical variations caused by subject variations. Furthermore, we have employed the Particle Swarm Optimization technique to tune the controller gains. Efficacy of the proposed algorithm method is experimentally demonstrated using a seven degree of freedom upper limb assist exoskeleton robot. The proposed algorithm was found to estimate the desired motion and assist accordingly. This algorithm in conjunction with an upper limb assist exoskeleton robot may be very useful for elderly people to perform daily tasks.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1753-1758
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• 2005

Human Adaptive Mechatronics (HAM), which is a system concept to adapt human characteristics, has been proposed. As the HAM application, this paper addresses an information emphasis scheme to alert some hazards which are undetectable by a human operator. The emphasis scheme employs cognitive psychological approach to human discrimination characteristics because excess or deficient emphasis may disturb the operation. One of advantages of teleoperation system is able to include human valuable abilities as global environment recognition, planning, prediction and so on. To implement these abilities to mechanical system is difficult because of not enough intelligence. Proposed teleoperation system is designed to progress the human abilities, and moreover, to not disturb the abilities. In this paper, we consider that the discrimination characteristics depend on window positions on GUI display and operator's individuality. Finally, the efficiency of the alert scheme is verified by some experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.163-169
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• 2008

In this paper, we propose a real-time people tracking system with multiple CCD cameras for security inside the building. The camera is mounted from the ceiling of the laboratory so that the image data of the passing people are fully overlapped. The implemented system recognizes people movement along various directions. To track people even when their images are partially overlapped, the proposed system estimates and tracks a bounding box enclosing each person in the tracking region. The approximated convex hull of each individual in the tracking area is obtained to provide more accurate tracking information. To achieve this goal, we propose a method for 3D walking human tracking based on the IMPRESARIO framework incorporating cascaded classifiers into hypothesis evaluation. The efficiency of adaptive selection of cascaded classifiers have been also presented. We have shown the improvement of reliability for likelihood calculation by using cascaded classifiers. Experimental results show that the proposed method can smoothly and effectively detect and track walking humans through environments such as dense forests.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.787-796
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• 2014

Many mobile robot navigation methods utilize laser scanners, ultrasonic sensors, vision camera, and so on for detecting obstacles and path following. However, human utilizes only vision(e.g. eye) information for navigation. In this paper, we study a mobile robot control method based on only the camera vision. The Gaussian Mixture Model and a shadow removal technology are used to divide the foreground and the background from the camera image. The mobile robot uses a combined CAMSHIFT and KLT feature tracker algorithms based on the information of the foreground to follow a person. The algorithm is verified by experiments where a person is tracked and followed by a robot in a hallway.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.331-336
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• 2008

In this paper, we propose a real-time people tracking system with multiple CCD cameras for security inside the building. To achieve this goal, we present a method for 3D walking human tracking based on the IMPRESARIO framework incorporating cascaded classifiers into hypothesis evaluation. The efficiency of adaptive selection of cascaded classifiers has been also presented. The camera is mounted from the ceiling of the laboratory so that the image data of the passing people are fully overlapped. The implemented system recognizes people movement along various directions. To track people even when their images are partially overlapped, the proposed system estimates and tracks a bounding box enclosing each person in the tracking region. The approximated convex hull of each individual in the tracking area is obtained to provide more accurate tracking information. We have shown the improvement of reliability for likelihood calculation by using cascaded classifiers. Experimental results show that the proposed method can smoothly and effectively detect and track walking humans through environments such as dense forests.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1745-1748
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• 2005

Near-infrared spectroscopy (NIRS) can be used to monitor brain activation by measuring changes in the concentration of oxy- and deoxy-hemoglobin (Hb) by their different spectra in the near-infrared range. Because NIRS is a noninvasive, highly flexible and portable device, it is very suitable to study brain activation when a human repeatedly performs a manipulative task, and possibly provides useful information to construct human adaptive mechatronics (HAM). There is some evidence that the dorsolateral prefrontal cortex (DLPFC) plays a major role in working memory and it is proposed that the use of working memory decreases as a human develops manipulative skills. In the present study, we investigated the activation of the dorsolateral prefrontal cortex (DLPFC) of the brain in Brodmann's areas 9 and 46 in drawing tasks to examine whether NIRS can measure the changes of DLPFC activation as a human develops manipulative skills. Subjects performed a mirror image drawing task and a square drawing task by ones' left hands. In the mirror image task the subject drew following a star shape based on a mirror image of it, but square drawing did not involve mirror image and was estimated to be simpler. The changes of the concentration of oxy-Hb was higher in the mirror image drawing than the square drawing in most subjects. The changes of oxy-Hb decreased as the subject repeated the drawing task in most subjects. In conclusion, The activation of DLPFC measured by NIRS can reflect the brain activity in the development of manipulative skills.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.877-881
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• 2008

In this paper, we propose a real-time people tracking system with multiple CCD cameras for security inside the building. The camera is mounted from the ceiling of the laboratory so that the image data of the passing people are fully overlapped. The implemented system recognizes people movement along various directions. To track people even when their images are partially overlapped, the proposed system estimates and tracks a bounding box enclosing each person in the tracking region. The approximated convex hull of each individual in the tracking area is obtained to provide more accurate tracking information. To achieve this goal, we propose a method for 3D walking human tracking based on the IMPRESARIO framework incorporating cascaded classifiers into hypothesis evaluation. The efficiency of adaptive selection of cascaded classifiers have been also presented. We have shown the improvement of reliability for likelihood calculation by using cascaded classifiers. Experimental results show that the proposed method can smoothly and effectively detect and track walking humans through environments such as dense forests.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.273-283
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• 2023

Education has recently witnessed a rapid increase in the use of edutech worldwide. This study focuses on Korean workers and explores an edutech-based learning model for vocational education and training. Based on analyses of edutech cases and interviews with edutech experts, a draft edutech model was designed and the validity was evaluated based on two Delphi surveys with a panel of experts in the field. The study's findings suggest that edutech-based employee education and training should prioritize LXP orientation (last CVR=1, last Mean=4.70) , implement adaptive learning through learning analytics (last CVR=1, last Mean=4.90), enhance the human touch effect using edutech (last CVR=1, last Mean=4.90), and emphasize the importance of designing curricula that apply edutech in a step-by-step learning process while incorporating suitable instructional design for the key technologies involved in vocational training programs. In addition, it was revealed that there is a strong need to implement a method that makes each stage of the learning process more effective (before, during, and after). Edutech-based vocational training program should consider the interests of all stakeholders, including learners, instructors, vocational training institutions, and government agencies. Given the promotion of government-sponsored vocational training projects in Korea, the findings of this research are likely to have significant implications for the future of Korea's education and training policies.