受人类婴儿发育启发的机器人手眼协调方法

An Approach to Robot Hand-eye Coordination Inspired by Human Infant Development

本研究的目的是建立一种通过机器人自主学习实现机器人手眼协调能力的方法,从而使机器人在真实环境中具有更高的自适应性.该方法受到人类婴儿发育过程的启发,首先构建了仿脑计算结构,模仿人类脑部在实现手眼协调过程中各个脑叶区域的配合过程;并提取人类婴儿在形成手眼协调的发育过程中的行为特征.使用该行为特征与仿脑计算结构相结合,建立一种新型的机器人手眼协调的学习算法.通过实验验证上述方法,结果表明:所建立的机器人控制学习系统可以实现机器人的手眼协调能力,并且可以让机器人表现出具有阶段性行为变化的这一类似人类发育过程的特征;同时在学习过程中机器人表现出高效的学习速度.

The objective of this research is to implement an autonomous learning approach to robotic hand-eye coordina- tion 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.