• 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.

• ETRI Journal
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• v.40 no.4
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• pp.483-498
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• 2018

Nowadays, with progresses in robotic science, the design and implementation of a mechanism for human-robot interaction with a low workload is inevitable. One notable challenge in this field is the interaction between a single human and a group of robots. Therefore, we propose a new comprehensive framework for single-human multiple-robot remote interaction that can form an efficient intelligent adaptive interaction (IAI). Our interaction system can thoroughly adapt itself to changes in interaction context and user states. Some advantages of our devised IAI framework are lower workload, higher level of situation awareness, and efficient interaction. In this paper, we introduce a new IAI architecture as our comprehensive mechanism. In order to practically examine the architecture, we implemented our proposed IAI to control a group of unmanned aerial vehicles (UAVs) under different scenarios. The results show that our devised IAI framework can effectively reduce human workload and the level of situation awareness, and concurrently foster the mission completion percentage of the UAVs.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.717-722
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• 2003

A driving simulator is a computer-controlled tool to study an interface between a driver and vehicle response by enabling the driver to participate in judging vehicle characteristics. Using the driving simulator, human factor study, vehicle system development and other research can be effectively done under controllable, reproducible and non-dangerous conditions. An Adaptive Cruise Control (ACC) system is generally regarded as a system that can be achieved in the near future without the demanding infrastructure components and technologies. ACC system is an automatic vehicle following system with no human engagement in the longitudinal vehicle direction. And the influence of the driver is substantial in developing the system. Driving characteristic is very different according to the accident riskiness, gender, age and so on. In this research, experiments have been carried out to investigate driving characteristics with the ACC system, using a driving simulator. Participants are 21 male and 19 female. Driving characteristics such as preferred headway-time, lane keeping ability, eye direction, and head movement have been observed and compared between the driving with ACC and the driving without ACC.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.473-482
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• 2015

Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.131-139
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• 2016

Recognition of human motions has become a main area of computer vision due to its potential human-computer interface (HCI) and surveillance. Among those existing recognition techniques for human motions, head detection and tracking is basis for all human motion recognitions. Various approaches have been tried to detect and trace the position of human head in two-dimensional (2D) images precisely. However, it is still a challenging problem because the human appearance is too changeable by pose, and images are affected by illumination change. To enhance the performance of head detection and tracking, the real-time three-dimensional (3D) data acquisition sensors such as time-of-flight and Kinect depth sensor are recently used. In this paper, we propose an effective feature extraction method, called adaptive local binary pattern (ALBP), for depth image based applications. Contrasting to well-known conventional local binary pattern (LBP), the proposed ALBP cannot only extract shape information without texture in depth images, but also is invariant distance change in range images. We apply the proposed ALBP for head detection and tracking in depth images to show its effectiveness and its usefulness.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3041-3043
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• 2000

GUI(graphical user interface) has been the dominant platform for HCI(human computer interaction). The GUI-based style of interaction has made computers simpler and easier to use. However GUI will not easily support the range of interaction necessary to meet users' needs that are natural, intuitive, and adaptive. In this paper we study an approach to track a hand in an image sequence and recognize it, in each video frame for replacing the mouse as a pointing device to virtual reality. An algorithm for real time processing is proposed by estimating of the position of the hand and segmentation, considering the orientation of motion and color distribution of hand region.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.111-114
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• 2001

In this paper, we supposed teller following algorithm that using sound localization for developing dialog type humanoid robot. A sound localization is studied for develop the techniques of an efficient 3-D sound system based on the psychoacoustics of spatial hearing with multimedia or virtual reality. When a robot talk with human, it is necessary that robot follow human for improved human interface and adaptive noise canceling. We apply this algorithm to robot system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.378-381
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• 2002

In this paper, we proposed an electromyography(EMG) based control method of a virtual robot arm as an adaptive human supporting system or remote control system, which consists of an shoulder control part, elbow control part, and wrist control part. The system uses four surface electrodes to acquire the EMG signal from operator. It is shown from the experiments that the EMG patterns during arm motions can be classified sufficiently by using SOM and LVQ. The interface system based on PC environment is constructed to 3-D graphic user interface(GUI) program. Experimental results show that proposed method obtains approximately 94 percent of success in classification.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.529-536
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• 2017

The general ground control system has control and information display functions for the operation of a single unmanned aerial vehicle. Recently, the function of the single ground control system extends to the operation of multiple UAVs. As a result, operators have been exposed to more diverse tasks and are subject to task overload due to various factors during their mission. This study proposes an adaptive ground control system that reflects the operator's condition through the task overload measurement of multiple UAV operators. For this, the ground control software is developed to control multiple UAVs at the same time, and the simulator with six degree-of-freedom aircraft dynamics is constructed for realistic human-machine-interface experiments by the operators.