• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.910-917
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• 2007

Of the possible interactions between human and robot, touch is an important means of providing human beings with emotional relief. However, most previous studies have focused on interactions based on voice and images. In this paper. a method of recognizing human touching behaviors is proposed for developing a robot that can naturally interact with humans through touch. In this method, the recognition process is divided into pre-process and recognition Phases. In the Pre-Process Phase, recognizable characteristics are calculated from the data generated by the touch detector which was fabricated using force sensors. The force sensor used an FSR (force sensing register). The recognition phase classifies human touching behaviors using a multi-layer perceptron which is a neural network model. Experimental data was generated by six men employing three types of human touching behaviors including 'hitting', 'stroking' and 'tickling'. As the experimental result of a recognizer being generated for each user and being evaluated as cross-validation, the average recognition rate was 82.9% while the result of a single recognizer for all users showed a 74.5% average recognition rate.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.3
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• pp.309-315
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• 2015

This paper presents a lower-limb exoskeleton testbed and its control method. An exoskeleton is a wearable robotic system that can enhance wearer's muscle power or assist human's movements. Among a variety of its applications, especially for military purpose, a wearable robot can be very useful for carrying heavy loads during locomotion by augmenting soldiers' mobility and endurance. The locomotion test on a treadmill was performed up to maximum 4km/h walking speed wearing the lower-limb exoskeleton testbed with a 45kg backpack load.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1188-1203
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• 2020

The human expression contains a lot of information that can be used to detect complex conditions such as pain and fatigue. After deep learning became the mainstream method, the traditional feature extraction method no longer has advantages. However, in order to achieve higher accuracy, researchers continue to stack the number of layers of the neural network, which makes the real-time performance of the model weak. Therefore, this paper proposed an expression recognition framework based on densely concatenated convolutional neural networks to balance accuracy and latency and apply it to humanoid robots. The techniques of feature reuse and parameter compression in the framework improved the learning ability of the model and greatly reduced the parameters. Experiments showed that the proposed model can reduce tens of times the parameters at the expense of little accuracy.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.67-73
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• 2016

With the rapid development of mobile services and the prevalence of education robots, robots are being developed to become a part of our lives and they can be utilized to assist teachers in giving education or learning to students. This standard has been proposed to define the degree of autonomy for education robot. The autonomy is an ability to perform a given work based on current state and sensor value without human intervention. The degree of autonomy is a scale indicating the extent of autonomy and it is determined in between 1 and 10 by considering the level of work and human intervention. It has been adapted as per standard and education robots can be utilized in teaching the students autonomously. Education robots can be beneficial in education and it is expected to contribute in assisting the teacher's education.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.223-231
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• 2014

Humanoid robot is the most suitable robot platform for effective human interaction and various intelligent services. The present work addresses development of real time wireless control application of humanoid robot's forward and backward walks, and turning in walking. For convenience of human users, the application is developed on Android OS (Operating System) working on his or her smartphone. To this end, theoretic background on various-directional biped walking is proposed based on joint trajectories for forward walking, which have been shaped with a global optimization method. In this paper, backward walking is scheduled by interchange of angles and angular velocities and additional change of signs in angular velocities at all the via-points connecting cubic polynomial trajectories. Turning direction in walking is also implemented by activating the transversal hip joint initially located in the support leg in two stages. After validation of the proposed walking schemes with Matlab simulator, a smartphone application for the omnidirectional walking has been developed to control a humanoid robot platform named DARwIn-OP interconnected via Wi-Fi. Experiment result of the present wireless control of a humanoid robot with smartphone is successful, and the application will be released in application market near future.

• 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 KIPS Transactions:PartD
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• v.14D no.6
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• pp.657-664
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• 2007

URC robot offers necessary service anytime and anywhere by using a network to the robot, expanding the applicable service, keeping all the functions in itself, it undertakes functions for the causing problems through the network. URC software components are composed of HRI(Human Robot Interaction), robot action technology and others. We analyze the quality models based on ISO/IEC 9126, define URC components evaluation specification consists of 4 parts such as generic rule, instance rule, evaluation value and test method. And we define the quality process and test case design for URC, and show a testing and evaluation process for URC components.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.78-86
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• 2014

This paper proposes a method of tracking an object for a person-following mobile robot by combining a monocular camera and a laser scanner, where each sensor can supplement the weaknesses of the other sensor. For human-robot interaction, a mobile robot needs to maintain a distance between a moving person and itself. Maintaining distance consists of two parts: object tracking and person-following. Object tracking consists of particle filtering and online learning using shape features which are extracted from an image. A monocular camera easily fails to track a person due to a narrow field-of-view and influence of illumination changes, and has therefore been used together with a laser scanner. After constructing the geometric relation between the differently oriented sensors, the proposed method demonstrates its robustness in tracking and following a person with a success rate of 94.7% in indoor environments with varying lighting conditions and even when a moving object is located between the robot and the person.

• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.70-78
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• 2015

The purpose of this study was to investigate how young children recognize the image of robots, and how they understand the relationship between themselves and robots based on school experience. 20 children from kindergarten A had no direct experience with educational robots, whereas 20 children from kindergarten B had experience in using educational robots in their classroom. Total 40 children from age group 5 class participated in this study. We collected data using interview and drawing test. The findings of the study are as follows: First, participating children recognized robots as having both the character of a machine and a human. But children with previous robot experience provided description of robots as a machine-tool. Both groups were not able to explain the structure of robots in details. Second, participating children understood that they can develop a range of social relationships with robots, including simple help to family replacement. There were mixed views on robots among the children with previous experience, but children with no experience described robots as taking the role of peers or family members. These findings could contribute to the development of robots and related programs in the field of early childhood education.

• Journal of Distribution Science
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• v.22 no.2
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• pp.103-113
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• 2024

Purpose: With the popularity of artificial intelligence (AI) in the service industry and occurrence ofservice failures in AI-based services, understanding human-robot interaction issues in service failure situations is especially important. Some issues which deserve further empirical investigation are whether consumers can develop the same tolerance for chatbots after service failure as they have for human agents, and the relationship between agent type and tolerance is mediated by the mechanisms of perceived warmth and perceived competence. Research Design, Data, and Methodology: This research experimentally collected and analyzed data from 119 university students who had experienced chatbots service failures. Differences in tolerance towards human agents and chatbots after experiencing service failures were explored, with a further examination of the mediating pathways between this relationship via perceived warmth and perceived competence. Results: Consumers are more tolerant ofservice failure with chatbots compared to service failure with human agents. Significant mediation of the relationship between service agent and service failure tolerance by perceived competence, while perceived warmth has no significant mediating effect. Conclusions: This research enhances our understanding of AI-assisted services, human-computer interaction, improves the service functionality of existing smart devices, and deepens the understanding of the relationship between consumer responses and behaviors.