Abstract
Robots are commonly used in harsh environments where it is difficult for humans to carry out dangerous tasks. Robot imitations provide a natural approach for humanoid robots to mimic the behavior of humans in real time. However, it is never an easy task to build an efficient and robust imitation system because of the high degree of freedom involved in motions. In this paper, we propose a human imitation system based on the Aldebaran NAO robot and the Microsoft Kinect, which can mimic the motions of the whole body in real time. By solving inverse kinematics through an optimization process, motions are split up into critical frames which are represented by a list of robot joint angles. Each joint angle is then derived through the control of the joint motors in NAO. In addition, balance maintenance in both the single and double supporting phases as well as the self-collision avoidance are taken into consideration. Experimental results show that the system is robust and flexible enough to imitate various human motions.
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Acknowledgments
This work is supported by the National High-Tech Research and Development Program of China (863 Program) (Grant No. 2015AA042303), the National Natural Science Foundation of China (Grant Nos. 61273335 & 61271005), the Hundred Talents Program of the Chinese Academy of Sciences (Grant No. Y14406), the Guangdong Innovative Research Team Program (201001D0104648280), and the Shenzhen Fundamental Research Programs (JCYJ20120831180626842, JCYJ20140718102705295).
