An Approach to Robot Hand-eye Coordination Inspired by Human Infant Development
ZHANG Xin, ZHOU Changle, JIANG Min, CHAO Fei
Fujian Provincial Key Laboratory of Brain-like Intelligent Systems, Cognitive Science Department, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China
The objective of this research is to implement an autonomous learning approach to robotic hand-eye coordination ability, so as to bring higher adaptive ability to robots in the practical environment. The approach is inspired by human infant's developmental procedure, a brain-like computational structure is constructed to simulate human brain cortices of controlling hand-eye coordination; and then, a behavioral pattern is adopted from infant development when forming hand-eye coordination. The combination of the computational structure and the behavioral pattern is applied to building a novel robotic hand-eye coordination learning algorithm. This work is supported by experimental evaluation, which shows that this approach is able to drive the robot to learn hand-eye coordination successfully; the robot also shows staged behavior change, which is similar to the features of human infant development; in addition, the robot exhibits fast learning speed.
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