• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1427-1434
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• 2021

In this paper, we propose a psychological state estimation process that computes children's attention and tension in response to training stimuli. Joint attention was adopted as the training stimulus required for behavioral intervention, and the Discrete trial training (DTT) technique was applied as the training protocol. Three types of training stimulation contents are composed to check the user's attention and tension level and provided mounted on a character-shaped tabletop robot. Then, the gaze response to the user's training stimulus is estimated with the vision-based head pose recognition and geometrical calculation model, and the nervous system response is analyzed using the PPG and GSR bio-signals using heart rate variability(HRV) and histogram techniques. Through experiments using robots, it was confirmed that the psychological response of users to training contents on joint attention could be quantified.

• Journal of The Korean Association of Information Education
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• v.11 no.2
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• pp.231-241
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• 2007

With a focus on LabView language to program Lego Mindstoms Robot in afterschool class to help children develop their special ability and aptitude. The purpose of this research was to make proposal for programming learning method using a robot as an algorithm learning tool to improve creative problem solving ability. To do this, robot programming training program in the amount of 30th period and teaching aids thereof were developed, and 6th grade primary school children were taught up to 30th period, then after, they were evaluated accordingly. Results from analysis of evaluation of achievement level with a focus on outcomes according to each period revealed that learners understood most of contents of curriculum. In view of such results from evaluation, it is judged that the curriculum as well as teaching aids that devised and created have been constituted in order that school children will be able to have developed a shared understanding of their learning sufficiently, and to put it into practice easily. Through these hands-on experiences in the course of researches, researcher could have confirmed the possibility of success for robot-programming training class as new creative algorithm learning tool in the primary school curriculum.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.833-839
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• 2010

In this paper, a novel 1 DOF hand rehabilitation robot is proposed in consideration of ADL training for stroke patients. To perform several ADL trainings, the proposed robot can move the thumb part and the part of 4 fingers simultaneously and realize the full ROM (Range of Motion) in grasp. Based on these characteristics, the proposed robot realizes several types of grasp such as cylindrical grasp, lateral grasp, and pinch grasp by using a passive revolute joint that can change the thumb movement direction. The movement of the thumb is driven by a cable mechanism and the part of 4 fingers is moved by a four-bar linkage mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.308-313
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• 2005

For a real-time quadruped robot running control, there are many important objectives to consider. In this paper, the running control architecture based on global states, which describe the cyclic target motion, and central pattern is proposed. The main goal of the controller is how the robot can have robustness to an unpredictable environment with reducing calculation burden to generate control inputs. Additional goal is construction of a single framework controller to avoid discontinuities during transition between multi-framework controllers and of a training-free controller. The global state dependent neuron network induces adaptation ability to an environment and makes the training-free controller. The central pattern based approach makes the controller have a single framework, and calculation burden is resolved by extracting dynamic equations from the control loop. In our approach, the model of the quadruped robot is designed using anatomical information of a cat, and simulated in 3D dynamic environment. The simulation results show the proposed single framework controller is robustly performed in an unpredictable sloped terrain without training.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1413-1415
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• 2004

This paper proposes a SVM(Support Vector Machine) training algorithm to control a service robot with voice command. The service robot with a stereo vision system and dual manipulators of four degrees of freedom implements a User-Dependent Voice Control System. The training of SVM algorithm that is one of the statistical learning theories leads to a QP(quadratic programming) problem. In this paper, we present an efficient SVM speech recognition scheme especially based on less learning data comparing with conventional approaches. SVM discriminator decides rejection or acceptance of user's extracted voice features by the MFCC(Mel Frequency Cepstrum Coefficient). Among several SVM kernels, the exponential RBF function gives the best classification and the accurate user recognition. The numerical simulation and the experiment verified the usefulness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.338-344
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• 2002

In this paper, neural network force tracking control is proposed. The conventional impedance function is reformulated to have direct farce tracking capability. Neural network is used to compensate for all the uncertainties such as unknown robot dynamics, unknown environment stiffness, and unknown environment position. On line training signal of farce error for neural network is formulated. A large x-y table is built as a test-bed and neural network loaming algorithm is implemented on a DSP board mounted in a PC. Experimental studies of farce tracking on unknown environment for x-y table robot are presented to confirm the performance of the proposed technique.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.496-499
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• 1999

This paper describes a medular neural network(MNN) for a vision system which tracks a given object using a sequence of images from a camera unit. The MNN is used to precisely recognize the given robot endeffector and to minize the processing time. Since the robot endeffector can be viewed in many different shapes in 3-D space, a MNN structure, which contains a set of feedforwared neural networks, co be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training patterns for a neural network share the similar charateristics so that they can be easily trained. The trained MNN is less sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.147-149
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• 2022

This paper proposes a state machine design methodology in which an interactive robot that mimics discrete trial training (DTT protocol) can support social interaction training for children with autism. The robot applied to social interaction training uses the response to the provided training stimulus as a quantitative indicator by processing the data received from the sensors measuring the behavioral response of the child. In this process, the state machine is used as information that classifies the state of the acquired data and provides the subsequent stimulus for DTT protocol. Through the joint attentional training, it can be used as evidence-based treatment information by quantitatively classifying the data on the number of sustainable and DTT protocol and the child's response, as well as the current reaction status of the child to the observer performing remote monitoring. At the same time, it was confirmed that it is possible to properly respond to misrecognition situations.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.315-322
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• 2009

This paper explains a control and navigation algorithm of a 6-DOF gait rehabilitation robot, which can allow a patient to navigate in virtual reality (VR) by upper and lower limbs interactions. In gait rehabilitation robots, one of the important concerns is not only to follow the robot motions passively, but also to allow the patient to walk by his/her intention. Thus, this robot allows automatic walking velocity update by estimating interaction torques between the human and the upper limb device, and synchronizing the upper limb device to the lower limb device. In addition, the upper limb device acts as a user-friendly input device for navigating in virtual reality. By pushing the switches located at the right and left handles of the upper limb device, a patient is able to do turning motions during navigation in virtual reality. Through experimental results of a healthy subject, we showed that rehabilitation training can be more effectively combined to virtual environments with upper and lower limb connections. The suggested navigation scheme for gait rehabilitation robot will allow various and effective rehabilitation training modes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.587-593
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• 2017

In this paper, we propose a method to solve the difficulties in constructing an environment capable of practical training on the theoretical contents of robot control field. We make a two-wheeled mobile robot with Segway structure using LEGO block. In order to demonstrate the validity of using the developed robot as a practical application of advanced control theory of robotics education such as dynamic system and nonlinear system, the robot takes a stable posture while balancing the change of gravity during running. The results of the experiment are shown. By presenting the results, the robots made using the LEGO block are used for practical training of advanced control theory of robotics. It can be used as a tool.