• 드라이브 ㆍ 컨트롤
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• 제15권3호
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• pp.1-7
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• 2018

Humanoid robots have fascinated many researchers since they appeared decades ago. For the requirement of both accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Humanoid robots are highly nonlinear, coupled, complex systems, accordingly the calculation of robot model is difficult and even impossible if precise model of the humanoid robots are unknown. Therefore, it is difficult to control using traditional model-based techniques. To realize model-free torque control, time-delay control (TDC) for humanoid robot was proposed with time-delay estimation technique. Using optimal walking trajectory obtained by particle swarm optimization, TDC with proposed scheme is implemented on whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the proposed TDC for humanoid robots.

• 한국기계가공학회지
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• 제15권2호
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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.

• 센서학회지
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• 제33권1호
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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.

• 로봇학회논문지
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• 제3권4호
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• pp.287-299
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• 2008

People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권6호
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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.

• 드라이브 ㆍ 컨트롤
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• 제17권1호
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• pp.44-50
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• 2020

For the requirement of accurate tracking control and the safety of physical human-robot interaction, torque control is basically desirable for humanoid robots. Because of the complexity of humanoid robot dynamics, the TDC (time-delay control) is practical because it does not require a dynamic model. However, there occurs a considerable error due to discontinuous non-linearities. To solve this problem, the TDC-FLC (fuzzy logic compensator) is applied to humanoid robots. The applied controller contains three factors: a TDE (time-delay estimation) factor, a desired error dynamic factor, and FLC to suppress the TDE error. The TDC-FLC is easy to execute because it does not require complicated humanoid dynamic calculations and the heuristic fuzzy control rules are intuitive. TDC-FLC is implemented on the whole body of a humanoid, not on biped legs even though it is performed by a virtual humanoid robot. The simulation results show the validity of the TDC-FLC for humanoid robots.

• 제어로봇시스템학회논문지
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• 제12권4호
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• pp.315-319
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• 2006

Support vector machines in biped humanoid robot are presented in this paper. The trajectory of the ZMP in biped walking robot poses an important criterion for the balance of the walking robots but complex dynamics involved make robot control difficult. We are establishing empirical relationships based on the dynamic stability of motion using SVMs. SVMs and kernel method have become very popular method for learning from examples. We applied SVM to model the practical humanoid robot. Three kinds of kernels are employed also and each result has been compared. As a result, SVM based on kernel method have been found to work well. Especially SVM with RBF kernel function provides the best results. The simulation results show that the generated ZMP from the SVM can be improve the stability of the biped walking robot and it can be effectively used to model and control practical biped walking robot.

• 한국항행학회논문지
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• 제21권1호
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• pp.132-137
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• 2017

본 논문에서는 로봇의 구조나 보행 상황을 반영해 하나의 보행 패턴을 다른 보행 패턴으로 변환하게 해주는 영모멘트 점 (ZMP; zero moment point)와 질량 중심 (CoM; center of mass)의 실시간 변환 방법을 제안한다. 일반적으로 휴머노이드 로봇은 높이와 질량과 같은 자체적인 구조 특성을 가지고 있다. 이러한 구조적 특성으로 인해 인간 또는 휴머노이드 로봇으로부터 측정되거나 생성되어진 CoM / ZMP 보행 패턴을 다른 로봇에 직접 적용하는 것은 어렵다. 이를 위하여 간단한 휴머노이드 로봇 모델인 cart-table model을 사용해 보폭의 길이, 보행 시간, CoM 높이 변화에 따라 보행 패턴의 특성을 분석한다. 그러한 분석으로부터 변환 방정식을 유도하고 시뮬레이션을 통해 제안된 방법을 검증한다.

• 한국정밀공학회지
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• 제26권4호
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• pp.72-81
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• 2009

The purpose of this paper is to accomplish the stable humanoid robot walking on the soft terrains. The goal of the humanoid robot development is to make the robotic system perform some tasks in human living environment. However, human dwelling environments are very different from those of laboratories, where varied experiments are performed by the robot. In many cases, the ground is soft or elastic unlike the floor of a laboratory. When a robot walks on the soft ground, the sole of robot contacts the uneven ground. This results in unstable walking or walking may be impossible according to the degree of softness. Therefore, the algorithm that facilitates stable walking on the soft ground surface is required. In this paper, we suggest an algorithm that controls the ankle to help the robot walk stably on the soft ground using the humanoid robot (ISHURO-II) as a real model. A humanoid robot walking on the soft ground was simulated to verify that the proposed algorithm results in stable walking.

• 로봇학회논문지
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• 제2권3호
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• pp.282-287
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• 2007

Humanoid and android robots are emerging as a trend shifts from industrial robot to personal robot. So human-robot interaction will increase. Ultimate objective of humanoid and android would be a robot like a human. In this aspect, implementation of robot's facial expression is necessary in making a human-like robot. This paper proposes a dynamic emotion model for a mascot-type robot to display similar facial and more recognizable expressions.