基于推算定位和超声波定位融合的机器人自主定位技术

针对室内环境下的机器人定位问题,首先介绍了用鳊码器进行推算定位的原理和算法,为了解决在长距离导航时带来的累积误差.在机器人移动过程中,超声波传感器与已知路标的距离实现精确测量的前提下,通过卡尔曼滤波算法对测量数据进行融合,修正累积定位的误差,进行精确定位.实验结果表明,该方法从原理上是可行的,可以应用到机器人的定位导航中.

Self-positioning of robot based on dead reckoning and ultrasonic data fusion

Self-positioning is the basic research of robot localization guidance. According to the robot movement under indoor environment, the encoder dead reckoning theory and algorithms were presented and then Kalman filter algorithms were used to integrate the encoder and ultrasonic data which resolved the accumulated error caused by long-distance navigation in a single sensor. The structure and algorithms were tested through simulation.