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ABSTRACT: This work presents a methodology to generate dynamically stable whole-body motions for a humanoid robot, which are converted from human motion capture data. The methodology consists of the kinematic and dynamical mappings for human-likeness and stability, respectively. The kinematic mapping includes the scaling of human foot and Zero Moment Point (ZMP) trajectories considering the geometric differences between a humanoid robot and a human. It also provides the conversion of human upper body motions using the method in. The dynamic mapping modifies the humanoid pelvis motion to ensure the movement stability of humanoid whole-body motions, which are converted from the kinematic mapping. In addition, we propose a simplified human model to obtain a human ZMP trajectory, which is used as a reference ZMP trajectory for the humanoid robot to imitate during the kinematic mapping. A human whole-body dancing motion is converted by the methodology and performed by a humanoid robot with online balancing controllers.
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on; 11/2009
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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 11-15, 2009, St. Louis, MO, USA; 01/2009
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ABSTRACT: This paper proposes CORBA-based visual servoing system of humanoid robot. To effectively control the humanoid robot which is connected to network, it needs to define necessary services for visual servoing as distribution object, and realize them in the middleware. For realizing it following services should be addressed. Naming service for searching a necessary service with unique name assigned to each object, image service for supplying image obtained from stereo camera. In the experiment, we show the result of balloon tracking and bursting that the robot tracks balloons as target objects in the real time, and if a balloon stop for a certain time, then the robot bursts the balloon.
SICE, 2007 Annual Conference; 10/2007
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ABSTRACT: During the communication and interaction with a human using motions or gestures, a humanoid robot needs to not only look like a human but also behavior like a human to avoid confusions in the communication and interaction. Among human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle that is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, response surface method (RSM). Then, a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate human-like arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of hand. An example motion was performed using the KIST humanoid robot, MAHRU
Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on; 11/2006
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ABSTRACT: Abstract—This work presents a methodology to generate dynamically stable whole-body motions for a humanoid robot, which are converted from human motion capture data. The methodology consists of the kinematic and dynamical mappings for human-likeness and stability, respectively. The kinematic mapping includes the scaling of human foot and Zero Moment Point (ZMP) trajectories considering the geometric differences between a humanoid robot and a human. It also provides the conversion of human upper body motions using the method in [1]. The dynamic mapping modifies the humanoid pelvis motion to ensure the movement stability of humanoid wholebody motions, which are converted from the kinematic mapping. In addition, we propose a simplified human model to obtain a human ZMP trajectory, which is used as a reference ZMP trajectory for the humanoid robot to imitate during the kinematic mapping. A human whole-body dancing motion is converted by the methodology and performed by a humanoid robot with online balancing controllers.
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[show abstract]
[hide abstract]
ABSTRACT: During the communication and interaction with a human using motions or gestures, a humanoid robot needs to not only look like a human but also behavior like a human to avoid confusions in the communication and interaction. Among human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle that is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, response surface method (RSM). Then, a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate human-like arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of hand. An example motion was performed using the KIST humanoid robot, MAHRU
