一种基于支持度的机器人足球系统全局地图构建方法

A Global Map Construction Method of the Robot Football System Based on Support Degree

由于机器人传感器的自身精度和足球比赛环境中未知的外界干扰,使得机器人的观测值精度受到影响,从而导致比赛中全局地图的构建不够精确。针对上述情况,采用一种基于支持度的全局地图构建方法。该方法利用相对距离的定义以及模糊集合理论中隶属度函数的优点,通过挖掘多机器人观测值间的相互支持程度,进而合理地分配各观测值在融合过程中所占的权重,达到构建出精确的全局地图的目的。通过仿真实例,验证该方法的有效性。

Due to the sensor accuracy and the unknown noises from the circumstance in the game, the accuracy of the observation of the robot will be more or less influenced, which lead to the inaccuracy of the global map construction in the game. So proposes a method of universal map construction based on support degree. This method uses the definition of relative distance and the advantages of the membership function in the fuzzy set theory, through the mining of the intersupport degree among the observations of the robots, reasonably distributes each observation with the weight in the fusing process, which attains the goal of constructing the global map accurately. Through simulation examples, verifies the validity of the method.