动态环境视觉导航的有限状态粗集方法研究

Study on Visual Navigation in Dynamic Environment Based on Finite-State Rough Set Theory

为实现移动机器人在多目标动态环境下导航与控制,提出了有限状态机和粗糙集理论相结合的单PT(Pan-Tilt)视觉系统监控策略.首先定义了目标方位信息可信度估计模型及基于动态优先级的目标选定方法.然后确定了每个目标监控的有限状态机模型,并依据粗糙集理论对目标监控决策表进行了约简,引入了非值约简描述方法,得到了最小规则集.在多目标环境下的移动机器人实验,验证了所提出方法的有效性.

A monitoring strategy for visual navigation in multi-object environment with only one PT（Pan-Tilt） camera based on rough set theory under finite-state machine frame is propoe, ed. The model to estimate the refiabihty level of multi-object orientation and an algorithm to calculate the objects priority are defined firstly. Then a finite-state machine model to monitoring each object is put fore- word. A minimal rule set for monitoring multi-object is achieved by using reduction algorithm of rough set theory. Also a description method＇of reduction based on not-value property is propoe, ed which is not included in the classical rough set theory.The validity and practicabihty of the strategy are proved by the experiments accomplished by using autonomous mobile robots to finish certain tasks in multi-object environment.