基于局部特征预测的栅格地图创建

为解决利用声纳传感器进行地图创建时容易出现检测不到障碍物或产生虚假障碍物的问题，提出了一种利用局部几何特征提高地图精确度和可靠性的方法．利用连续几次可靠的声纳信息预测机器人周围局部环境中几何特征的位置与方向，并根据几何特征计算当前声纳数据的置信度．在全局地图更新中，删除置信度低于设定阈值的声纳数据，从而根据置信度降低不确定信息对地图创建的影响．实验结果证明本方法可以有效地提高地图的精确度．

Grid map building based on prediction of local features

In order to build more precise and stable map with sonar sensors, a method based on prediction of local geometrical features is proposed. The position and orientation of features in the robot's local space are predicted from reliable sonar readings, and confidence measures are assigned to each sonar reading to indicate the probability that it is reliable. The confidence values are used to weaken the effect of uncertain sonar readings on the global map, and to discard the readings completely if the confidence value is sufficiently low. Experiments carried out on Pioneer2 robot prove that the method performs well.