• 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.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.404-407
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• 2003

In this paper, we have designed the humanoid robot's leg parts with 12 D.O.F. This robot uses ankle's joints to confirm stability of walking performance. It is less movable to use ankle's joints than to do upper body's balancing joints like IWR-III, which needs three parts of via points, support leg, swing leg and balancing joints. Instead, the proposed humanoid robot needs support leg and swing leg via points. ZMP(Zero Moment Point) is utilized to guarantee the stability of robot's walking. The humanoid robot uses the ankle's joints to compensate for IWR-III's balancing joints movement. Actually we concern about a motor performance when making a real humanoid robot. So a simulator is employed to know each joint torque of humanoid robot. This simulator needs D-H(Denavit-Hartenberg) parameters, robot's mass property and two parts of via points. The simulation results are robot's walking trajectories and each motor torque. Using the walking trajectories, we can see the robot's walking scene with 3D simulator. Before we develop the humanoid robot, simulation of the humanoid robot's walking performance is very helpful. And the torque data will be used to make humanoid's joint module.

• Journal of Drive and Control
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• v.15 no.3
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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.

• 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 Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.167-173
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• 2007

This paper describes a redundancy resolution based method for determining an optimal initial configuration of a humanoid robot for holding an object. There are three important aspects for a humanoid robot to be able to hold an object. Those three aspects are the reachability that guarantees the robot to reach the object, the stability that guarantees the robot to remain stable while moving or holding the object, and the manipulability that makes the robot manipulate the object dexterously. In this paper, a humanoid robot with 20 degrees of freedom is considered. The humanoid robot is kinematically redundant and has infinite number of solutions for the initial configuration problem. The complex three-dimensional redundancy resolution problem is divided into two simple two-dimensional redundancy resolution problems by incorporating the symmetry of the problem, robot's moving capability, and the geometrical characteristics of the given robot. An optimal solution with respect to the reachability, the stability, and the manipulability is obtained by solving these two redundancy resolution problems.

• The Journal of Korea Robotics Society
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• v.3 no.4
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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.

• 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.

• 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 KSME Conference
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• 2007.05a
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• pp.933-938
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• 2007

These days, up-to-date humanoid robots are continuously developed. Among them, Qrio, Asimo[1,2] are famous for its unique walking technology and natural movement. These robots could show manufacturers' technological improvement and leave a good impression to the customer. In accordance with global trends, Samsung is also producing humanoid robot. The humanoid robot, however, could walk like a human compared to the industrial robot fixed in the factory. This feature could cause another dynamic effect while walking. In this paper, the robot's feet were examined to find out parameters that affect stability of the humanoid robot's feet. With the sensitivity analysis, the optimization procedure in design of experiments finds the most suitable performance of robot. Maximum deflection of the frame upon various cases was minimized, and rubber coefficients for shock absorption were optimized.

• 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.