• Journal of the HCI Society of Korea
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• v.3 no.2
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• pp.1-8
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• 2008

We introduce VRSMS(VR-based sensor management system) which is the visualization system of micro-scale air quality monitoring system Airscope[3]. By adopting VR-based visualization method, casual users can get insight of air quality data intuitively. Users can also manipulate sensors in VR space to get specific data they needed. For adaptive visualization, we separated visualization and interaction methods from air quality data. By separation, we can get consistent way for data access so new visualization and interaction methods are easily attached. As one of the adaptive visualization method, we constructed large display system which consists of several small displays. This system can provide accessibility for air quality data to people one public space.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3283-3292
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• 2022

Based on the Deep Q-Network(DQN) algorithm of reinforcement learning, an active fault-tolerance method with incremental action is proposed for the control system with sensor faults of the once-through steam generator(OTSG). In this paper, we first establish the OTSG model as the interaction environment for the agent of reinforcement learning. The reinforcement learning agent chooses an action according to the system state obtained by the pressure sensor, the incremental action can gradually approach the optimal strategy for the current fault, and then the agent updates the network by different rewards obtained in the interaction process. In this way, we can transform the active fault tolerant control process of the OTSG to the reinforcement learning agent's decision-making process. The comparison experiments compared with the traditional reinforcement learning algorithm(RL) with fixed strategies show that the active fault-tolerant controller designed in this paper can accurately and rapidly control under sensor faults so that the pressure of the OTSG can be stabilized near the set-point value, and the OTSG can run normally and stably.

• Korean Journal of Computational Design and Engineering
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• v.21 no.1
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• pp.20-30
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• 2016

Recently immersive virtual reality (VR) becomes popular due to the advanced development of I/O interfaces and related SWs for effectively constructing VR environments. In particular, natural and intuitive manipulation of 3D virtual objects is still considered as one of the most important user interaction issues. This paper presents a comparative study on the manipulation and interaction of 3D virtual objects using different interfaces and interactions in three VR environments. The comparative study includes both quantitative and qualitative aspects. Three different experimental setups are 1) typical desktop-based VR using mouse and keyboard, 2) hand gesture-supported desktop VR using a Leap Motion sensor, and 3) immersive VR by wearing an HMD with hand gesture interaction using a Leap Motion sensor. In the desktop VR with hand gestures, the Leap Motion sensor is put on the desk. On the other hand, in the immersive VR, the sensor is mounted on the HMD so that the user can manipulate virtual objects in the front of the HMD. For the quantitative analysis, a task completion time and success rate were measured. Experimental tasks require complex 3D transformation such as simultaneous 3D translation and 3D rotation. For the qualitative analysis, various factors relating to user experience such as ease of use, natural interaction, and stressfulness were evaluated. The qualitative and quantitative analyses show that the immersive VR with the natural hand gesture provides more intuitive and natural interactions, supports fast and effective performance on task completion, but causes stressful condition.

• Interaction and multiscale mechanics
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• v.3 no.3
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• pp.257-266
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• 2010

A novel resonance based proximity DC current sensor is proposed. The sensor consists of a piezo sensed and actuated cantilever beam with a permanent magnet mounted at its free end. When the sensor is placed in proximity to a wire carrying DC current, resonant frequency of the beam changes with change in current. This change in resonant frequency is used to determine the current through the wire. The structure is simulated in micro and meso scale using COMSOL Multi physics software and the sensor is found to be linear with good sensitivity.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.363-370
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• 2014

Despite several years of intense research, the security and cryptography in wireless sensor networks still have a number of ongoing problems. This paper describes how identification (ID)-based node authentication can be used to solve the key agreement problem in a three-layer interaction. The scheme uses a novel security mechanism that considers the characteristics, architecture, and vulnerability of the sensors, and provides an ID-based node authentication that does not require expensive certificates. The scheme describes the routing process using a simple ID suitable for low power and ID exposure, and proposes an ID-based node authentication. This method achieves low-cost communications with an efficient protocol. Results from this study demonstrates that it improves routing performance under different node densities, and reduces the computational cost of key encryption and decryption.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.24-29
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• 2013

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the "physical sensor fusion" method, which generates the trajectory of a robot based upon the environment model and sensory data, a "command fusion" method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.

• The KIPS Transactions:PartA
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• v.16A no.4
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• pp.255-262
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• 2009

We present an autonomous entertainment dolphin robot system based on ubiquitous sensor networks(USN). Generally, It is impossible to apply to USN and GPS in underwater bio-mimetic robots. But An Entertainment dolphin robot which presented in this paper operates on the water not underwater. Navigation of the underwater robot in a given area is based on GPS data and the acquired position information from deployed USN motes with emphasis on user interaction. Body structures, sensors and actuators, governing microcontroller boards, and swimming and interaction features are described for a typical entertainment dolphin robot. Actions of mouth-opening, tail splash or water blow through a spout hole are typical responses of interaction when touch sensors on the body detect users' demand. Dolphin robots should turn towards people who demand to interact with them, while swimming autonomously. The functions that are relevant to human-robot interaction as well as robot movement such as path control, obstacle detection and avoidance are managed by microcontrollers on the robot for autonomy. Distance errors are calibrated periodically by the known position data of the deployed USN motes.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.19-29
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• 2022

Natural user interface (NUI) is used for the natural motion interface without using a specific device or tool like a mouse, keyboards, and pens. Recently, as non-contact sensor-based interaction technologies for recognizing human motion, gestures, voice, and gaze have been actively studied, an environment has been prepared that can provide more diverse contents based on various interaction methods compared to existing methods. However, as the number of sensors device is rapidly increasing, the system using a lot of sensors can suffer from a lack of computational resources. To address this problem, we proposed a real-time multi-device control system for natural interactive platform. In the proposed system, we classified two types of devices as the HC devices such as high-end commercial sensor and the LC devices such astraditional monitoring sensor with low-cost. we adopt each device manager to control efficiently. we demonstrate a proposed system works properly with user behavior such as gestures, motions, gazes, and voices.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.677-684
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• 2009

With various sensor network and ubiquitous technologies, we can extend interaction area from a virtual domain to physical space domain. This spatial interaction is differ in that traditional interaction is mainly processed by direct interaction with the computer machine which is a target machine or provides interaction tools and the spatial interaction is performed indirectly between users with smart interaction tools and many distributed components of space. So, this interaction gives methods to users to control whole manageable space components by registering and recognizing objects. Finally, this paper provides an effective spatial interaction method with template-based task mapping algorithm which is sorted by historical interaction data for support of users' intended task. And then, we analyze how much the system performance would be improved with the task mapping algorithm and conclude with an introduction of a GUI method to visualize results of spatial interaction.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.169-176
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• 2020

This paper studied the collision detection of robot manipulators for safe collaboration in human-robot interaction. Based on sensor-based collision detection, external torque is detached from subtracting robot dynamics. To detect collision using joint torque sensor data, a comparative study was conducted using data-based machine learning algorithm. Data was collected from the actual 3 degree-of-freedom (DOF) robot manipulator, and the data was labeled by threshold and handwork. Using support vector machine (SVM), decision tree and k-nearest neighbors KNN method, we derive the optimal parameters of each algorithm and compare the collision classification performance. The simulation results are analyzed for each method, and we confirmed that by an optimal collision status detection model with high prediction accuracy.