• 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.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.203-209
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• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• 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.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.551-558
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• 2008

This paper deals with the real-time stable walking for a humanoid robot, ISHURO-II, on uneven terrain. A humanoid robot necessitates achieving posture stabilization since it has basic problems such as structural instability. In this paper, a stabilization algorithm is proposed using the ground reaction forces, which are measured using FSR (Force Sensing Resistor) sensors during walking, and the ground conditions are estimated from these data. From this information the robot selects the proper motion pattern and overcomes ground irregularities effectively. In order to generate the proper reaction under the various ground situations, a fuzzy algorithm is applied in finding the proper angle of the joint. The performance of the proposed algorithm is verified by simulation and walking experiments on a 24-DOFs humanoid robot, ISHURO-II.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.161-166
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• 2011

This paper addresses the vision based autonomous walking control system. To handle the obstacles which exist beyond the field of view(FOV), we used the 3d panoramic depth image. Moreover, to decide the avoidance direction and walking motion of a humanoid robot for the obstacle avoidance by itself, we proposed the vision based path planning using 3d panoramic depth image. In the vision based path planning, the path and walking motion are decided under environment condition such as the size of obstacle and available avoidance space. The vision based path planning is applied to a humanoid robot, URIA. The results from these evaluations show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a practical humanoid robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.225-228
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• 2002

인터넷 기술의 눈부신 발전으로 더 이상 VRML이 브라우저 상에서 3차원 오브젝트만을 보여 주는 시기는 지났다. 온라인 가상 환경에서 3차원 캐릭터를 통해서 가상의 공간에서 현실로 넘나들고자 하는 욕구 역시 증대되고 있다. 다시 말해서, 사용자들은 3차원 웹 상에서 자신의 움직임과 같은 Humanoid를 만들어 현실감을 느끼고 싶어한다. 본 논문에서는 웹 브라우저로 쉽게 접근 할 수 있는, VRML(Virtual Reality Modeling Language)구조를 통해 Humanoid를 생성한다. 그리고 컴퓨터가 만들어낸 가상에서 인간의 움직임에 대한 체험을 하도록 하는 Humanoid를 생성하여 사용자와 상호 작용할 수 있는 방법을 제안하고 이를 구현하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.107-113
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• 2010

In this paper, a prototype of cooperative work model for multi-robots system is introduced and the evolutionary approach is applied to generate the motions for the cooperative works of multi-robots system using genetic algorithm. The cooperative tasks can be performed by a humanoid robot and a mobile robot to deliver objects from shelves. Generation of the humanoid motions such as pick up, rotation, and place operation for the cooperative works are evolved. Modeling and computer simulation for the cooperative robots system are executed in Webots environments. Experimental results show the feasible and reasonable solutions for humanoid cooperative tasks are obtained.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.683-689
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• 2014

The paper introduces dynamic generation technique of foot trajectories for humanoid robots using CPG(Central Pattern Generator) and proposes adaptive walking method for slope terrains combining a feedback network. The proposed CPG based technique generates the trajectory of foot in the Cartesian coordinates system and it can change the step length adaptively according to the feedback information. To cope with variable slope terrains, the sensory feedback network in the CPG are designed using the geometry relationship between foot position and body center position such that humanoid robot can maintain its stability. To demonstrate the effectiveness of the proposed approach, the experiments on humanoid robot Nao are executed in the Webot simulation. The performance and motion features of the CPG based approach are compared and analyzed focusing on the adaptability in slope terrains.

• 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.