摘要
针对里程计在定位过程中存在累积误差的问题,建立了一种通用的移动机器人里程计误差模型,对里程计误差进行实时反馈补偿.在利用激光雷达进行环境特征提取过程中,根据激光雷达原始数据存在的误差,建立了激光雷达的观测误差模型,并根据环境特征和机器人的相对位置关系,建立了移动机器人观测模型.最后,结合里程计和激光雷达误差模型,利用扩展卡尔曼滤波(EKF)实现了基于环境特征跟踪的移动机器人定位.实验结果验证了里程计和激光雷达误差模型的引入,在增加较短定位时间的情况下,可以有效地提高移动机器人的定位精度.
For the accumulated errors of the odometry in the process of localization, a general odometry error model for mobile robots is established to compensate the odometry errors via feedback in real time. According to the errors of original data from the laser radar, an observation error model for laser radar is established. The observation model for mobile robots is designed according to the environmental features and the relative position of mobile robots. Further, extended Kalman filter is used by combining the odometry and laser radar error model to realize the mobile robots＇ localization based environmental feature tracking. The experimental results illustrate that the location accuracy of the robots is improved effectively with increasing a little locating time by introducing odometry and laser radar error model.
出处
《信息与控制》
CSCD
北大核心
2012年第4期406-412,共7页
Information and Control
