Chaotic dynamics of a behavior-based miniature mobile robot: effects of environment and control structure
Chaotic dynamics of a behavior-based miniature mobile robot: effects of environment and control structure
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DOI：
10.1016/j.neunet.2004.09.002
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发表时间：
2005-03
期刊：
影响因子：
--
通讯作者：
M. Islam;K. Murase
中科院分区：
文献类型：
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作者：
M. Islam;K. Murase
为了研究自主行为的规律性和复杂性，将自主移动的机器人在各种条件下获得的感知信息流作为一个复杂系统进行分析。采集了小型移动的机器人在自由航行过程中的感觉信息时间序列Xn，并绘制在返回地图上，得到Xn+τvs. Xn.该图显示出特征轨迹，代表了时间序列的规律性。相关积分和李雅普诺夫指数分析也显示了确定性混沌的性质，分形维数和正李雅普诺夫指数的存在。在机器人与三个不同的神经控制器中获得的感官信息的分析表明，自主机器人的行为方式，感官信息的流动是由一个确定性的规则，这种模式是唯一的每个控制器。此外，在各种环境下的分析表明，从一个轨迹到另一个返回地图上的过渡发生在自主行为的过程中。在不同条件下计算的分形维数和李雅普诺夫维数表明，这些维数可以用来量化自主行为的复杂性和任务的相对难度。在不同进化阶段的分析表明，行为表现与分形维数相关。这些研究使用了一个微型移动的机器人，允许理想化的实验条件下，坚定地证明了复杂的分析，可用于自主系统和行为的评估和优化。
To study the regularity and complexity of autonomous behavior, the flow of sensory information obtained in autonomous mobile robots under various conditions was analyzed as a complex system. Sensory information time series Xnwas collected from a miniature mobile robot during free navigation, and plotted on the return map, the graph of Xn+τvs. Xn. The plot exhibited a characteristic trajectory, representing the regularity of the time series. Correlation integral and Lyapunov exponent analysis also showed properties of deterministic chaos; the presence of fractal dimension and positive Lyapunov exponent. Analysis of sensory information obtained in the robot with three different neural controllers revealed that the autonomous robot behaves in such a way that the flow of sensory information is governed by a deterministic rule, and this pattern is unique to each controller. Furthermore, the analysis in various environments exhibited that transitions from one trajectory to another on the return map occur during the course of autonomous behavior. The fractal and Lyapunov dimensions calculated in various conditions indicate that these dimension could be utilized to quantify the complexity of autonomous behavior and the relative difficulty of tasks. Analyses at different evolutionary stage revealed that behavioral performance correlates with fractal dimension. These studies using a miniature mobile robot that allowed to idealize the experimental conditions demonstrated firmly that the complex analysis could be utilized in evaluation and optimization of autonomous systems and the behavior.