Abstract
In general, human dance is created by the imagination and innovativeness of human dancers, which in turn provides an inspiration for robotic choreography generation. This paper proposes a novel mechanism for a humanoid robot to create good choreography autonomously with the imagination of human dance. Such a mechanism combines innovativeness with the characteristic preservation of human dance, and enables a humanoid robot to present the characteristics of “imitation, memory, imagination, process and combination”. The proposed mechanism has been implemented on a real humanoid robot, NAO, to verify its feasibility and performance. Experimental results are presented to demonstrate good performance of the proposed mechanism.
Highlights
Social robots are emerging with various forms such as assistants, pets and servants, which show social intelligence in human style, based on deep models of human cognition and social competence [1,2]
Inspired by the imagination used in human dance creation, this paper proposes a mechanism of creating robotic choreography autonomously by a humanoid robot with imagination
Visual C++ is used for implementing the method of imagination (Section 3), and Webots is used for showing the effect of the dance objects on a simulated NAO robot
Summary
Social robots are emerging with various forms such as assistants, pets and servants, which show social intelligence in human style, based on deep models of human cognition and social competence [1,2]. These robots have played an important role in our society, e.g., serving the elderly people as companions at their homes. In our taxonomy [3], the creation of robotic choreography is an important research category for robotic dance, and it emphasizes that the robot should develop its autonomous ability based on its embodied environment or human/machine aesthetic consciousness (or cognition). The autonomous creation of robotic choreography, which draws lessons from the mature experiences of human dance creation, is still inadequate and has been rarely explored so far
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