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EN
For an effective human-robot collaboration, it is important that an assistive robot is able to forecast a human action. The new action recognition method for anticipating the human activities basis on visual observation is presented. The spatio-temporal human-object relation taking into account the so-called affordance is analyzed, the action features are defined. We also deliver a RGB-D type activity dataset obtained using new Senz3D vision sensors. To demonstrate the effectiveness of the proposed approach, we discuss the experiments with summarizing the anticipation results obtained using two different datasets.
EN
This paper aims at developing a real-time, robust, and reliable behaviors for an omnidirectional soccer robot, can be used in crowded dynamically-changing environments. The soccer robot system consists of highly coordinated operations and movements so as to fulfill specific objectives, even under unfavorable situations. The associated issues are position control, velocity control and sensing information in addition to the need for imitating the human-like decision. The proposed method considers not only the kinematics of the robot but also its dynamics. Moreover, a control structure is designed and several behaviors for a soccer robot are proposed. Image processing, recognition and target following algorithm are illustrated through experiments.
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