• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.238-246
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• 2013

In this paper, a robot vision technique is presented to detect obstacles, particularly approaching humans, in the images acquired by a mobile robot that autonomously navigates in a narrow building corridor. A single low-cost color camera is attached to the robot, and a trapezoidal area is set as a region of interest (ROI) in front of the robot in the camera image. The lower parts of a human such as feet and legs are first detected in the ROI from their appearances in real time as the distance between the robot and the human becomes smaller. Then, the human detection is confirmed by detecting his/her face within a small search region specified above the part detected in the trapezoidal ROI. To increase the credibility of detection, a final decision about human detection is made when a face is detected in two consecutive image frames. We tested the proposed method using images of various people in corridor scenes, and could get promising results. This method can be used for a vision-guided mobile robot to make a detour for avoiding collision with a human during its indoor navigation.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.135-143
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• 2003

This paper presents the impact minimization of a biped robot by using genetic algorithm. In case we want to accomplish the designed plan under the special environments, a robot will be required to have walking capability and patterns with legs, which are in a similar manner as the gaits of insects, dogs and human beings. In order to walk more effectively, studies of mobile robot movement are needed. To generate optimal motion for a biped robot, we employ genetic algorithm. Genetic algorithm is searching for technology that can look for solution from the whole district, and it is possible to search optimal solution from a fitness function that needs not to solve differential equation. In this paper, we generate trajectories of gait and trunk motion by using genetic algorithm. Using genetic algorithm not only on gait trajectory but also on trunk motion trajectory, we can obtain the smoothly stable motion of robot that has the least impact during the walk. All of the suggested motions of biped robot are investigated by simulations and verified through the real implementation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.806-811
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• 2005

The robot to search and rescue is used in narrow space where human cannot approach. In case of this robot, it can overcome obstacles such as wrecks or stairs etc. Also, this robot can do various locomotion for each object. In this reason, an articulated robot has advantages comparing with one module robot. However, the existing articulated robot has limits to overcome vertical passages. For expanding contacted territory of robot, a novel mechanism is demanded. In this paper, the novel mechanism of articulated mobile robot is designed for moving level ground and vertical passages. This paper proposes to change wheel alignment. The robot needs two important motions for passing vertical passages like pipe. One is a motion to press wheels at wall for not falling into gravity direction. The other is a motion that wheels contact a vertical direction of wall's tangential direction for reducing loss of force. The mechanism of the robot focused that two motions can be acted to use just one motor. Length of each link of robot is optimized that wheels contact a vertical direction of wall's tangential direction through kinematic modeling of each link. The force of pressing wall of robot is calculated through dynamic modeling. This robot composes four modules. This mechanism is confirmed by dynamic simulation using ADAMS program. The articulated mobile robot is elaborated based on the results of kinematic modeling and dynamic simulation.

• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.1-8
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• 1999

To provide information service with time constraints, it is required to support real-time information system for retrieval and update of distributed information. In this paper, we propose an information retrieval system model for internet. We design and implement a Domain Administration-Oriented search engine for the regional information network. Accordingly, an intelligent robot gathering and updating distributed information is implemented. And, in order to improves the performance of the system, a realtime robot control policy based on the loads of network and web server is proposed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1259-1265
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• 2014

In this paper, the real-time attitude determination based Matlab using low-cost receivers was designed and evaluated. The GNSS attitude determination system was implemented to operation in real-time by TimerCallback in MATLAB. The TTM(Transmission Time Misalignment) of U-blox receiver was confirmed through zero baseline tests and this problem was revised. The computed attitude by the high-cost NovAtel receiver was compared to the computed attitude by the low-cost U-blox receiver. As a result of this, the performance of attitude determination systems by low-cost receiver was confirmed. To determine baseline, LAMBDA and BC-LAMBDA for integer ambiguities search methods were used. To confirm suitable integer ambiguity search method in real-time attitude determination algorithm, determined baselines by two methods were compared, and it was confirmed that BC-LAMBDA is more suitable. As a result of this, the operation of real-time attitude determination system was confirmed using 3 low-cost receivers.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.257-264
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• 2009

This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a mobile robot. The proposed approach can locate extremely small-sized face regions of $12{\times}12$ pixels. We solve a tiny face detection problem by organizing a system that consists of multiple detectors including a mean-shift color tracker, short- and long-rage face detectors, and an omega shape detector. The proposed method adopts the long-range face detector that is well trained enough to detect tiny faces at a long range, and limiting its operation to only within a search region that is automatically determined by the mean-shift color tracker and the omega shape detector. By focusing on limiting the face search region as much as possible, the proposed method can accurately detect tiny faces at a long distance even with a low-resolution image, and decrease false positives sharply. According to the experimental results on realistic databases, the performance of the proposed approach is at a sufficiently practical level for various robot applications such as face recognition of non-cooperative users, human-following, and gesture recognition for long-range interaction.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.127-132
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• 2016

For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.626-631
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• 2005

This paper presents the target object search algorithm under dynamic programming (DP) in the Tree-type maze. We organized an experimental environment with the concatenation Y-shape diverged way, small mobile robot, and a target object. By the principle of optimality, the backbone of DP, an agent recognizes that a given whole problem can be solved if the values of the best solution of certain ancillary problem can be determined according to the principle of optimality. In experiment, we used two different control algorithms: a left-handed method and DP. Finally we verified the efficiency of DP in the practical application using a real robot.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.1-7
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• 2022

Robots are widely used in industries and services. Traditional robots have been used to perform repetitive tasks in a fixed environment, and it is very difficult to solve a problem in which the physical interaction of the surrounding environment or other objects is complicated with the existing control method. Reinforcement learning has been actively studied as a method of machine learning to solve such problems, and provides answers to problems that robots have not solved in the conventional way. Studies on the learning of all physical robots are commonly affected by noise. Complex noises, such as control errors of robots, limitations in performance of measurement equipment, and complexity of physical interactions with surrounding environments and objects, can act as factors that degrade learning. A learning method that works well in a virtual environment may not very effective in a real robot. Therefore, this paper proposes a weighted sum method and a linear regression method as an effective and accurate learning method in a noisy environment. In addition, the bottle flipping was trained on a robot and compared with the existing learning method, the validity of the proposed method was verified.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.360-365
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• 2008

We propose an efficient robot name registration and recognition method in order to enable a Call-and-Come service for home robots. In the proposed method for the name registration, the search space is first restricted by using monophone-based acoustic models. Second, the registration of robot names is completed by using triphone-based acoustic models in the restricted search space. Next, the parameter for the utterance verification is calculated to reduce the acceptance rate of false calls. In addition, acoustic models are adapted by using a distance speech database to improve the performance of distance speech recognition, Moreover, the location of a user is estimated by using a microphone array. The experimental result on the registration and recognition of robot names shows that the word accuracy of speech recognition is 98.3%.