自主式微小型移动机器人群体行为进化的研究

BEHAVIOR EVOLUTION FOR AUTONOMOUS MICRO MOBILE ROBOT COLONY

自主式微小型移动机器人群体面临的一些环境常常是未知的、无结构的 ,同时由于其自身体积大小的限制 ,在目前的工业水平上也很难在其上安装一些较为先进的传感器 ,以致机器人仅能获取局部的信息 ,这些原因使得采用传统基于任务的设计方法将十分困难 ,而采用基于行为的设计方法时 ,也很难保证所设计的机器人行为的有效性 ,为此本文采用了遗传算法 ,随机产生了机器人群体中各初始个体的障碍物回避行为及机器设备故障排除行为 ,当群体在特定的工作环境中仿真运行时 ,根据环境的情况和所需实现的任务 ,使群体行为性能达到了较为优化的目的 .

The colony of autonomous micro mobile robot will run in some unknown and unstructured environment. There are many limits to autonomous micro mobile robot. These limits make the robot only know the part information about the environment and the robot can't remember many past statements. So it is very difficult to design the autonomous robot based on information. It is also difficult to ensure the robot behavior is very validity to its environment and its task when we design the autonomous micro mobile robot based on behavior. This paper presents a gene algorithm based on behavior. We design three kinds of base behavior: Obstacle avoidance behavior, fault repair behavior, and fault scout behavior. At the beginning of the gene algorithm,the coders of these behavior are produced at random. At the last the behavior of the colony and the robot are very good to the environment and the task when the colony runs in the simulation environment. The result shows this method is very validity.