• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.358-364
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• 2007

Intelligent walking modeling of humanoid robot using learning based neuro-fuzzy system is presented in this paper. Walking pattern, trajectory of the zero moment point (ZMP) in a humanoid robot is used as an important criterion for the balance of the walking robots but its complex dynamics makes robot control difficult. In addition, it is difficult to generate stable and natural walking motion for a robot. To handle these difficulties and explain empirical laws of the humanoid robot, we are modeling practical humanoid robot using neuro-fuzzy system based on the two types of natural motions which are walking trajectories on a t1at floor and on an ascent. Learning based neuro-fuzzy system employed has good learning capability and computational performance. The results from neuro-fuzzy system are compared with previous approach.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.376-382
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• 2005

In this paper, practical biped humanoid robot is presented, designed, and modeled by fuzzy system. The humanoid robot is a popular research area in robotics because of the high adaptability of a walking robot in an unstructured environment. But owing to the lots of circumstances which have to be taken into account it is difficult to generate stable and natural walking motion in various environments. As a significant criterion for the stability of the walk, ZMP (zero moment point) has been used. If the ZMP during walking can be measured, it is possible for a biped humanoid robot to realize stable walking by a control method that makes use of the measured ZMP. In this study, measuring the ZMP trajectories in real time situations throughout the whole walking phase on the flat floor and slope are conducted. And the obtained ZMP data are modeled by fuzzy system to explain empirical laws of the humanoid robot. By the simulation results, the fuzzy system can be effectively used to model practical humanoid robot and the acquired trajectories will be applied to the humanoid robot for the human-like walking motions.

• 전자공학회논문지 IE
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• v.45 no.2
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• pp.28-33
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• 2008

The paper is represented active robot soccer system using humanoid. many robot we implement the control method of several robot and the algorithm of robot soccer system. the position and direction of the robot is recognized quickly using color tag on the shoulder of robot and special personal computer. Humanoid robot soccer system in this paper develops better in existent wheel-driven soccer robot. Forward, through a lot of studies, self-moving soccer game like human with humanoid is possible.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.226-236
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• 2008

In this paper, control software architecture is designed to enable a heterogeneous multiple humanoid robot demonstration executing tasks cooperating with each other. In the heterogeneous humanoid robot team, one large humanoid robot and two small humanoid robots are included. For the efficient and reliable information sharing between many software components for humanoid control, sensing and planning, CORBA based software framework is applied. The humanoid tasks are given in terms of finite state diagram based human-robot interface, which is interpreted into the XML based languages defining the details of the humanoid mission. A state transition is triggered based on the event which is described in terms of conditions on the sensor measurements such as robot locations and the external vision system. In the demonstration of the heterogeneous humanoid team, the task of multiple humanoid cleaning the table is given to the humanoid robots and successfully executed based on the given state diagram.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.18-23
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• 2024

Humanoid robots, designed to interact in human environments, require stable mobility to ensure safety. When a humanoid robot falls, it causes damage, breakdown, and potential harm to the robot. Therefore, fall detection is critical to preventing the robot from falling. Prevention of falling of a humanoid robot requires an operator controlling a crane. For efficient and safe walking control experiments, a system that can replace a crane operator is needed. To replace such a crane operator, it is essential to detect the falling conditions of humanoid robots. In this study, we propose falling detection methods using Convolution Neural Network (CNN) model. The image data of a humanoid robot are collected from various angles and environments. A large amount of data is collected by dividing video data into frames per second, and data augmentation techniques are used. The effectiveness of the proposed CNN model is verified by the experiments with the humanoid robot MAX-E1.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.175-177
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• 2006

This paper deals with implementation of middleware using CAN(Controller Area Network) network and TCP/IP for real-time distributed control system of a humanoid robot. Existent system using CAN network is available. But, there is problems in extensibility and flexibility. In this raper, the new system using TCP/IP for solution and improvement of problems is proposed. The new system is applied to ISHURO-II, real-humanoid robot. The performance is verified through experiment.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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• pp.125-130
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• 2016

In this paper, we deal with the dynamic walking of a humanoid robot. In our method, the inverted pendulum model is used as a dynamic model for a humanoid robot in which the Zero Moment Point (ZMP) and COG constraints of the robot are analyzed by considering the motion of the robot as that of an inverted pendulum. The motion of a humanoid robot should be generated by considering the dynamics of the robot, which commonly requires a large amount of computation. If a robot walks from one position to another while keeping the ZMP in the stable region, then the robot remains dynamically stable. The linear inverted pendulum model regards the whole robot as a point mass. It is simple, and relatively less computation is needed; however, it cannot model the whole dynamics of a humanoid robot. We propose a method for modeling a humanoid robot as an inverted pendulum system having 14 point masses. We also show that the dynamic stability of a humanoid robot can be determined more precisely by our method.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.237-244
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• 2008

Nowadays, research on human-robot interaction has been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report a speaker localization system with six microphones for a humanoid robot called MAHRU from KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. The proposed method, using the TDOA-based feature matrix and its algorithm based on MSAE, effortlessly localizes a sound source without any requirement for calculating approximate nonlinear equations. To verify the solid performance of our speaker localization system for a humanoid robot, we present various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.43-43
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• 2000

In this paper, we introduce a case study of developing a miniature humanoid robot that has 16 degrees of freedom and is able to perform statically stable walking. The developed humanoid robot is 37cm tall and weighs 1,200g. RC servo motors are used as actuators. The robot can walk forward and turn to any direction on even surface. It equipped with a small digital camera, so it can transmit vision data to a remote host computer via wireless modem. The robot can be operated in two modes; One is a remote-controlled mode, in which the robot behaves according to the command given by a human operator through the user-interface program running on a remote host computer, the other is a stand-alone mode, in which the robot behaves autonomously according to the pre-programmed strategy. The user-interface program also contains a robot graphic simulator that is used to produce and verify the robot's gait motion. In our walking algorithm, the ankle joint is mainly used lot balancing the robot. The experimental results shows that the developed robot can perform statically stable walking on even surface.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.108-114
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• 2009

In this paper, we presents a behavior planning for humanoid robots using behavior primitive in 3 dimensional workspace. Also, we define behavior primitives that humanoid robot accomplishes various tasks effectively. Humanoid robot obtains information of the outside environment and its inner information from various sensors in complex workspace with various obstacles. We verify our approach on a developed small humanoid robot using embedded vision and sensor system in a experimental environment. The experimental results show that the humanoid robot performs its tasks fast and effectively.