• Journal of Engineering Education Research
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• v.13 no.2
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• pp.64-69
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• 2010

Electronics machines make daily human life more convenient and comfortable and try to ease burdens. When designing and manufacturing such mechatronic systems, the engineers need to have a wide range of knowledge. The purpose of our education is for students to learn to use mechatronic techniques. To realize our goal, we regard "an interest in creation" of our student as an important educational method. In this paper, we propose and try an educational method for mechatronics creation using "their interest". The method is to hold robot competitions between 1st and 3rd year students as a regular curriculum. In order to confirm the progress of our students in our engineering course, in the last year, some students entered the Rescue Robot Contest held in Kobe Japan. As a result, our student team got second place, a great honor considering it was our first attempt. We confirm that the robot competition is a useful method to make students study by themselves.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.237-246
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• 2011

Robots have been used in many fields due to its performance improvement and variety of its functionality, to the extent which robots can replace human tasks. Individual feature and better performance of robots are expected and required to be created. As their performances and functions have increased, systems have gotten more complicated. Multi mobile robots can perform complex tasks with simple robot system and algorithm. But multi mobile robots face much more complex driving problem than singular driving. To solve the problem, in this study, driving algorithm based on the energy method is applied to the individual robot in a group. This makes a cluster be in a formation automatically and suggests a cluster the automatic driving method so that they stably arrive at the target. The energy method mentioned above is applying attractive force and repulsive force to a special target, other robots or obstacles. This creates the potential energy, and the robot is controlled to drive in the direction of decreasing energy, which basically satisfies lyapunov function. Through this method, a cluster robot is able to create a formation and stably arrives at its target.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.933-934
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• 2006

High level perceptual tasks such as context understanding, SLAM and object recognition are essential for intelligent robot to provide services for human supports. Those intelligent robots often use camera sensor for vision information, sonar or laser sensor for range information, encoder for angular velocity of wheel and so on. The information is generated at different time intervals by the different H/W devices and S/W algorithms. The generation of high level information requires the specific mixture of low level information. And the information should be represented to be useful for robots to use in their ecological niche. In conventional robot systems, perceptual module requires the resource to use by tightly coupling whenever it is needed. So the resource and information cannot be easily shared and even could be invalid for the delayed information. In this paper, we propose a synchronization system of robot-centered information for context understanding. Our system represents information for the robot capacity and synchronizes the information that is asynchronously generated, where is employed the black-board architecture.

• Smart Structures and Systems
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• v.9 no.6
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• pp.535-547
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• 2012

Controlling the balance of motion in a context involving a biped robot navigating a rugged surface or a step is a difficult task. In the present study, a $3{\times}5$ flexible piezoelectric tactile sensor array is developed to provide a foot pressure map and zero moment point for a biped robot. We introduce an innovative concept involving structural electrodes on a piezoelectric film in order to improve the sensitivity. The tactile sensor consists of a polymer piezoelectric film, PVDF, between two patterned flexible print circuit substrates (FPC). Additionally, a silicon rubber bump-like structure is attached to the FPC and covered by a polydimethylsiloxane (PDMS) layer. Experimental results show that the output signal of the sensor exhibits a linear behavior within 0.2 N ~ 9 N, while its sensitivity is approximately 42 mV/N. According to the characteristic of the tactile sensor, the readout module is designed for an in-situ display of the pressure magnitudes and distribution within $3{\times}5$ taxels. Furthermore, the trajectory of the zero moment point (ZMP) can also be calculated by this program. Consequently, our tactile sensor module can provide the pressure map and ZMP information to the in-situ feedback to control the balance of moment for a biped robot.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.176-187
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• 2002

This paper focuses on the study of simulation and evolution of Micro Air Vehicles. Micro Air Vehicles or MAVs are small flying robots that are used for surveillance, search and rescue, and other missions. The simulated robots are designed based on realistic characteristics and the brains (controllers) of the robots are generated using genetic algorithms, i .e., simulated evolution. The objective for the experiments is to investigate the effects of robot team size and topology (simulation environment) on the evolution of simulated robots. The testing of team sizes deals with finding an ideal number of robots to be deployed for a given mission. The goal of the topology experiments is to see if there is an ideal topology (environment) to evolve the robots in order to increase their utility in most environments. We compare the results of the various experiments by evaluating the fitness values of the robots i .e., performance measure. In addition, evolved robot teams are tested in different situation in order to determine if the results can be generalized, and statistical analysis is performed to evaluate the evolved results.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.259-264
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• 2007

In this paper, we composed chaos mobile robot by embedding many type of chaos circuit including Arnold Equation and Chua's Equation and proposed method of evaluation of obstacles when it meets or approaches an obstacle while the mobile robot searches an any plane with chaos trajectory and method of concentrating search when it faces target and verified these results. For obstacles avoidance, we developed algorithm that evades an obstacles with chaos trajectory by assuming fixed obstacle, obstacles using VDP model, hidden obstacles using BVP model as obstacles and for searching an object, we developed algorithm of searching with a chaos trajectory by assuming BVP model as an object, verified the results and confirmed reasonability of them.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.2
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• pp.269-281
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• 2014

This paper examines the suitability of using the Computational Fluid Dynamics (CFD) tools, ANSYS-CFX, as an initial analysis tool for predicting the drag and propulsion performance (thrust and torque) of a concept underwater vehicle design. In order to select an appropriate thruster that will achieve the required speed of the Underwater Disk Robot (UDR), the ANSYS-CFX tools were used to predict the drag force of the UDR. Vertical Planar Motion Mechanism (VPMM) test simulations (i.e. pure heaving and pure pitching motion) by CFD motion analysis were carried out with the CFD software. The CFD results reveal the distribution of hydrodynamic values (velocity, pressure, etc.) of the UDR for these motion studies. Finally, CFD bollard pull test simulations were performed and compared with the experimental bollard pull test results conducted in a model basin. The experimental results confirm the suitability of using the ANSYS-CFX tools for predicting the behavior of concept vehicles early on in their design process.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.738-744
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• 2013

According to the cognitive science research, the interaction intent of humans can be estimated through an analysis of the representing behaviors. This paper proposes a novel methodology for reliable intention analysis of humans by applying this approach. To identify the intention, 8 behavioral features are extracted from the 4 characteristics in human-human interaction and we outline a set of core components for nonverbal behavior of humans. These nonverbal behaviors are associated with various recognition modules including multimodal sensors which have each modality with localizing sound source of the speaker in the audition part, recognizing frontal face and facial expression in the vision part, and estimating human trajectories, body pose and leaning, and hand gesture in the spatial part. As a post-processing step, temporal confidential reasoning is utilized to improve the recognition performance and integrated human model is utilized to quantitatively classify the intention from multi-dimensional cues by applying the weight factor. Thus, interactive robots can make informed engagement decision to effectively interact with multiple persons. Experimental results show that the proposed scheme works successfully between human users and a robot in human-robot interaction.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1193-1200
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• 2015

An effective swing trajectory of legged robots is different from the swing trajectories of humans or animals because of different dynamic characteristics. Therefore, it is important to find optimal parameters through experiments. This paper proposes a real-time nonlinear programming (RTNLP) method for optimization of the swing trajectory of the legged robot. For parameterization of the trajectory, the swing trajectory is approximated to parabolic and cubic spline curves. The robotic leg is position-controlled by a high-gain controller, and a cost function is selected such that the sum of the motor inputs and tracking errors at each joint is minimized. A simplified dynamic model is used to simulate the dynamics of a robotic leg. The purpose of the simulation is to find the feasibility of the optimization problem before an actual experiment occurs. Finally, an experiment is carried out on a real robotic leg with two degrees of freedom. For both the simulation and the experiment, the design variables converge to a feasible point, reducing the cost value.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.518-523
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• 2015

This paper proposes a gait phase classifier using a Recurrent Neural Network (RNN). Walking is a type of dynamic system, and as such it seems that the classifier made by using a general feed forward neural network structure is not appropriate. It is known that an RNN is suitable to model a dynamic system. Because the proposed RNN is simple, we use a back propagation algorithm to train the weights of the network. The input data of the RNN is the lower body's joint angles and angular velocities which are acquired by using the lower limb exoskeleton robot, ROBIN-H1. The classifier categorizes a gait cycle as two phases, swing and stance. In the experiment for performance verification, we compared the proposed method and general feed forward neural network based method and showed that the proposed method is superior.