• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.548-550
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• 2006

This paper deals with the implementation of a small humanoid robot controller on the basis of Real Time Operating System(RTOS) and the FPGA. This controller was adapted to the humanoid robot with 25 DOFs, which are 12 DOFs in each leg, 8 DOFs in each arm, 3 DOFs in waist, and 2 DOFs in head. The robot actuators were used DX-117 servo motors that have all of the controller components in one module in order to simplify the control structure. In addition, the main controller is FPGA of Virtex4-FX from Xilinx, and ported on VxWorks that is kind of RTOS. It is essential to install this RTOS on the complex control system and to do control activity at the multitasking environments. This paper suggested the method of distributing the computational load in the humanoid robot controller using the FPGA and RTOS concepts. All of the control process was verified through the real action of the humanoid.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.420-426
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• 2001

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 an 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 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 for balancing the robot. The experimental results shows that the developed robot can perform statically stable walking on an even surface.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.399-405
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• 2007

This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn't fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn't robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.77-79
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• 2004

Because robot hardware architecture generally is consisted of a few sensors and motors connected to the central processing unit, this type of structure is led to time consuming and unreliable system. For analysis, one of the fundamental difficulties in real-time system is how to be bounded the time behavior of the system. When a distributed control network controls the robot, with a central computing hub that sets the goals for the robot, processes the sensor information and provides coordination targets for the joints. If the distributed system supposed to be connected to a control network, the joints have their own control processors that act in groups to maintain global stability, while also operating individually to provide local motor control. We try to analyze the architecture of network-based humanoid robot's leg part and deal with its application using the CAN(Controller Area Network) protocol.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.95-97
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• 2005

This paper deals with the implementation of walking for a humanoid robot by ZMP measurement using wireless sensor network. ZMP is measured by FSR sensors which are mounted at each corner of a sole. The wireless sensor network collects the sensor data according and exchanges robot information between host PC and a robot system. The master controller mounted on robot body receives trajectory data from the host PC via sensor network and drives the joint motor based on trajectory data. The time scheduler of the master controller controls the events at the ratio of 100ms. With this configuration, the walking of the humanoid robot KHR-1 could be realized successfully.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.628-632
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• 2003

An intelligent miniature humanoid robot system is designed and implemented as a platform for researching walking algorithm. The robot system consists of a mechanical robot body, a control system, a sensor system, and a human interface system. The robot has 6 dofs per leg, 3 dofs per arm, and 2 dofs for a neck, so it has total of 20 dofs to have dexterous motion capability. For the control system, a supervisory controller runs on a remote host computer to plan high level robot actions based on the vision sensor data, a main controller implemented with a DSP chip generates walking trajectories for the robot to perform the commanded action, and an auxiliary controller implemented with an FPGA chip controls 20 actuators. The robot has three types of sensors. A two-axis acceleration sensor and eight force sensing resistors for acquiring information on walking status of the robot, and a color CCD camera for acquiring information on the surroundings. As an example of an intelligent robot action, some experiments on playing soccer are performed.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1169-1170
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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.

• Journal of Power System Engineering
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• v.21 no.5
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• pp.41-47
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• 2017

To implement Argentina tango dancer-like walking of the humanoid robot, a new trajectory generation scheme based on particle swarm optimization of the blending polynomial is presented. Firstly, the characteristics of Argentina tango walking are derived from observation of tango dance. Secondly, these are reflected in walking pose conditions and cost functions of particle swarm optimization to determine the coefficients of blending polynomial. For the stability of biped walking, zero moment point and reference trajectory of swing foot are also included in cost function. Thirdly, after tango walking cycle is divided into 3 stages with 2 postures, optimal trajectories of ankles, knees and hip of lower body, which include 6 sagittal and 4 coronal angles, are derived in consequence of optimization. Finally, the feasibility of the proposed scheme is validated by simulating biped walking of humanoid robot with derived trajectories under the 3D Simscape environment.

• Proceedings of the KIEE Conference
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• 2006.10b
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• pp.175-180
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• 2006

In this paper, we develope a type of humanoid robot which can express its emotion against human actions. To interact with human, the developed robot has several abilities to express its emotion, which are verbal communication with human through voice/image recognition, motion tracking, and facial expression using fourteen Servo Motors. The proposed humanoid robot system consists of a control board designed with AVR90S8535 to control servor motors, a framework equipped with fourteen server motors and two CCD cameras, a personal computer to monitor its operations. The results of this research illustrate that our intelligent emotional humanoid robot is very intuitive and friendly so human can interact with the robot very easily.