• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1115-1121
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• 2012

This paper proposes a method to extract accurate plane of an object in unstructured environment for a humanoid robot by using a laser scanner. By panning and tilting 2D laser scanner installed on the head of a humanoid robot, 3D depth map of unstructured environment is generated. After generating the 3D depth map around a robot, the proposed plane extraction method is applied to the 3D depth map. By using the hierarchical clustering method, points on the same plane are extracted from the point cloud in the 3D depth map. After segmenting the plane from the point cloud, dimensions of the planes are calculated. The accuracy of the extracted plane is evaluated with experimental results, which show the effectiveness of the proposed method to extract planes around a humanoid robot in unstructured environment.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.87-93
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• 2019

This research deals with posture optimization for humanoid robot against external forces using genetic algorithm and neural network. When the robot takes a motion to push an object, the torque of each joint is generated by reaction force at the palm. This study aims to optimize the posture of the humanoid robot that will change this torque. This study finds an optimized posture using a genetic algorithm such that torques are evenly distributed over the all joints. Then, a number of different optimized postures are generated from various the reaction forces at the palm. The data is to be used as training data of MLP(Multi-Layer Perceptron) neural network with BP(Back Propagation) learning algorithm. Humanoid robot can find the optimal posture at different reaction forces in real time using the trained neural network include non-training data.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.248-253
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• 2015

In order to adapt to human's life and perform missions, a humanoid robot needs a height at least similar with children's. In this paper, we proposed a humanoid robot which is like a child who is taller than 1m. We presented showing the humanoid robot's kinematics, designing of a three-dimensional model, developing mechanisms, and the hardware structures using servo motors and compact size PC. Through this process, we designed and manufactured child humanoid robot 'CHARLES(Cognitive Humanoid Autonomous Robot with Learning and Evolutionary Systems)' that is robot is 1m 10cm tall and 8.16kg in weight. For robot's walking, we applied to ZMP-based walking technique and the creation algorithm is applied for walking patterns. Through experiments, we analyzed walking patterns according to the creation and changing parameter values.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1029-1037
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• 2008

When a humanoid robot pushes an object with its force, it is essential to adequately control its posture so as to maximize the surplus torque far all joints. For such purpose, this study proposes a method to find an optimal posture of a humanoid robot using a genetic algorithm in such a way that the surplus torque for all joints is maximized. In this study, pushing motion of an 18-DOF humanoid robot is considered. When the robot takes a cooperative motion to push an object, the palms and soles are assumed to be fixed at the object and ground respectively, and are subjected to sense the reaction force from the object and the ground. Then, the torques for all joints are calculated and reflected to fitness function of the genetic algorithm. To verify the effectiveness of the proposed method, a number of simulations with different fitness functions are carried out. The simulation result shows that the proposed method can be adopted to find optimized posture in cooperative motion of a humanoid robot.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.84-92
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• 2006

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.485-492
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• 2006

This paper deals with implementation of network for distributed control system of a humanoid robot ISHURO(Inha Semyung Humanoid Robot). A humanoid robot needs much degree of freedom structurally and much data for having flexible movement. To realize such a humanoid robot, distributed control method is preferred to the centralized one since it gives a compactness, modularity and flexibility for the controllers. For organizing distributed control system of a humanoid robot, a control processor on a board is needed to individually control the joint motor and communication technology between the processors is required to transmit its information within control time. The processor is DSP-based processor and includes CAN network on a chip. It shares the computational load such as monitoring the sensor information and controlling the actuator between each of modules. In this paper, the communication architecture is suggested and its message protocol are discussed including message structure, time consumption for transmission, and controller structure at the view of distributed control for a humanoid robot. All of the sequence are simulated with Matlab and then verified with real walking experiment by ISHURO.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.289-290
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• 2009

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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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.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.73-80
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• 2008

Many researchers are studying on humanoid robots in all over the world. However the humanoid robots are still limited in doing works like picking up objects on the ground or moving rapidly. In this study, a humanoid robot based on the wheel-driving was developed. It can operate with a human working area keeping the stability. Also, the developed robot can take up the object on the floor since it has knee(1DoF) and waist(3DoF), and do service quickly and steadily. The hardware and software structure and algorithms of the developed robot, SEROPI are introduced in this paper.