• The Journal of Korea Robotics Society
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• v.10 no.2
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• pp.61-69
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• 2015

In this paper, we propose and examine the feasibility of the robot-assisted behavioral intervention system so as to strengthen positive response of the children with autism spectrum disorder (ASD) for learning social skills. Based on well-known behavioral treatment protocols, the robot offers therapeutic training elements of eye contact and emotion reading respectively in child-robot interaction, and it subsequently accomplishes pre-allocated meaningful acts by estimating the level of children's reactivity from reliable recognition modules, as a coping strategy. Furthermore, for the purpose of labor saving and attracting children's interest, we implemented the robotic stimulation configuration with semi-autonomous actions capable of inducing intimacy and tension to children in instructional trials. From these configurations, by evaluating the ability of recognizing human activity as well as by showing improved reactivity for social training, we verified that the proposed system has some positive effects on social development, targeted for preschoolers who have a high functioning level.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.42-52
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• 1997

Computer aided process planning and Offline programming are decisive factors in successful implementation of automated robotic production. However, conventional offline programming procedure has proven ineffective due to time-consuming teaching process for robot programming and due to inefficient system modeling. The paper presents an efficient procedure to semi-automatically generate robot job programs for ship block welding applications. In the research, the teaching positions are automatically determined by predefined rules which are functions of the type and the dimensions of the given welding section of ship block. And a sequence of robot movements and welding conditions such as welding type, welding current, welding speed, and welding torch orientation, are determined by use of Standard Program which is experimentally proved to work well for the welding wection group. Finally, a robot program for the welding section is generated automatically. Based on the algorithm, a offline automatic teaching software is developed. The paper presents also the algorithm and structure of the software.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.297-305
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• 2021

Monocular depth estimation helps the robot to understand the surrounding environments in 3D. Especially, deep-learning-based monocular depth estimation has been widely researched, because it may overcome the scale ambiguity problem, which is a main issue in classical methods. Those learning based methods can be mainly divided into three parts: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning trains the network from dense ground-truth depth information, unsupervised one trains it from images sequences and semi-supervised one trains it from stereo images and sparse ground-truth depth. We describe the basics of each method, and then explain the recent research efforts to enhance the depth estimation performance.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.181-183
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• 2006

This paper proposes an intelligent decision framework for update of the environment model using GSPN(generalized stochastic petri nets). The GSPN has several advantages over direct use of the Markov Process. The modeling, analysis, and performance evaluation are conducted on the mathematical basis. By adopting the probabilistic approach, our decision framework helps the robot to decide the time to update the map. The robot navigates autonomously for a long time in dynamic environments. Experimental results show that the proposed scheme is useful for service robots which work semi-permanently and improves dependability of navigation in dynamic environments.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1063-1066
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• 2014

The humanoid robot, DRC-HUBO is developed from the KHR (KAIST Humanoid Robot) series to meet the requirements of the DARPA Robotics Challenge. DARPA Robotics Challenge was a competition to develop semi-autonomous humanoid robot so that dispatched in dangerous environments in place of humans like the Fukushima nuclear accident. In this paper, we introduce DRCH-UBO briefly and a methodology to remove debris blocking an entryway. The methodology includes inverse kinematics for DRC-HUBO and stabilization controller based on ZMP. Proposed inverse kinematics is robust, and pelvis-related tasks improve the manipulability and workspace of the arms. The controller improves the damping characteristic of the system and mitigates the instability during removal of debris. For given position and orientation of the debris, DRC-HUBO generates motion to reach the debris and lift up while stabilizing itself. Many experimental results verify our proposed methodology.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.822-827
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• 2009

As research for URC robot to advance the robot system dissemination and pracical use becomes active, also interest for robot platform and standardization is increasing. However, URC robot middleware does not involve a convergence with IT. Although it seems to be a high connection between robots and IT, the existing middleware has not considered different environments, thus making convergence efforts difficult. The middleware should improve their functions in order to synchronize with IT and to interact through formatted messages. In this paper, we present the necessity of the formatted message in the development of URC platform. In addition, design of the message protocol for the convergence based on the analysis of RUPI, OPC and SECS-II.

• The Magazine of the IEIE
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• v.33 no.3 s.262
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• pp.49-55
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• 2006

인간과 로봇의 자연스러운 상호작용을 위하여 영상과 음성을 기반으로 한 인간-로봇 상호작용 (HRI: Human Robot Interaction) 기술들을 소개한다. URC개념의 서버/클라이언트 구조를 갖는 소프트웨어 로봇에 수행 가능한 얼굴 인식 및 검증, 준 생체정보(semi biometrics)를 이용한 사용자 인식, 제스처인식, 화자인식 및 검증, 대화체 음성인식 기술들에 대하여 살펴본다. 이러한 인간-로봇 상호작용 기술들은 초고속 인터넷과 같은 IT 인프라를 이용하는 URC(Ubiquitous Robotic Companion) 기반의 지능형 서비스 로봇을 위한 핵심기술로서 사용되어진다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1048-1053
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• 2005

This paper presents design and integration of the ROBHAZ-DT3, which is a newly developed mobile robot system with chained double-track mechanisms. A passive adaptation mechanism equipped between the front and rear body enables the ROBHAZ-DT3 to have good adaptability to uneven terrains including stairs. The passive adaptation mechanism reduces energy consumption when moving on uneven terrain as well as its simplicity in design and remote control, since no actuator is necessary for adaptation. Based on this novel mobile platform, a rescue version of the ROBHAZ-DT3 with appropriate sensors and a semi-autonomous mapping and localization algorithm is developed to participate in the RoboCup2004 US-Open: Urban Search and Rescue Competition. From the various experiments in the realistic rescue arena, we can verify that the ROBHAZ-DT3 is reliable in traveling rugged terrain and the proposed mapping and localization algorithm are effective in the unstructured environment with uneven ground. The another application is an military robot for an EOD(Explosive Ordnance Disposal) and reconnaissance mission. The military version of the ROBHAZ-DT3 with a water disrupter, a thermal scope and a long distance wireless communication device is developed and sent to the area of military tactics in Iraq. Consequently, the feasibility of the military version of ROBHAZ-DT3 is verified.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.17-29
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• 2017

IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user 's indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.701-706
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• 2007

Recently, a number of researches about linear magnetorheological(MR) damper using valve-mode characteristics of MR fluid have sufficiently undertaken, but researches about rotary MR damper using shear-mode characteristics of MR fluid are not enough. In this paper, we performed vibration control of shear-mode MR damper for unlimited rotating actuator of mobile robot. Also fuzzy logic based vibration control for shear-mode MR damper is suggested. The parameters, like scaling factor of input/output and center of the triangular membership functions associated with the different linguistic variables, are tuned by genetic algorithm. Simulation results demonstrate the effectiveness of the fuzzy-skyhook controller for vibration control of shear-mode MR damper under impact force.