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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >Chaotic dynamics of a behavior-based miniature mobile robot: effects of environment and control structure.
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Chaotic dynamics of a behavior-based miniature mobile robot: effects of environment and control structure.

机译:基于行为的微型移动机器人的混沌动力学:环境和控制结构的影响。

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摘要

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 Xn was collected from a miniature mobile robot during free navigation, and plotted on the return map, the graph of X(n+tau) vs. 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.
机译:为了研究自主行为的规律性和复杂性,将自主移动机器人在各种条件下获得的感觉信息流作为一个复杂系统进行了分析。感官信息时间序列Xn是在自由导航期间从微型移动机器人收集的,并绘制在返回图上,即X(n + tau)与Xn的关系图。该图显示了特征轨迹,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Lyapunov指数的存在。对在具有三个不同神经控制器的机器人中获得的感官信息进行的分析表明,自主机器人的行为方式是,感官信息的流动受确定性规则支配,并且该模式对于每个控制器都是唯一的。此外,在各种环境中的分析表明,在自主行为的过程中会发生从返回轨迹上的一条轨迹到另一条轨迹的过渡。在各种条件下计算的分形维数和Lyapunov维数表明,这些维数可用于量化自主行为的复杂性和任务的相对难度。不同进化阶段的分析表明,行为表现与分形维数相关。这些使用允许理想化实验条件的微型移动机器人进行的研究坚定地表明,复杂的分析可用于评估和优化自治系统及其行为。

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