【摘要】 针对室内移动机器人基于接收信号强度(RSSI,Received Signal Strength Indication)测距定位存在非视距(NLOS,Not-line-of-sight)传播问题,提出一种利用运动模型预测RSSI并修正NLOS测量的定位算法。首先结合移动机器人运动模型预测位置和信号强度RSSI,进而实现NLOS误差判定和测量修正;然后结合步长将移动机器人限制到圆域内,采用改进三边定位算法定位;最后使用扩展卡尔曼滤波(EKF,extended Kalman Filter)进行定位结果优化,得到位置的优化估计。仿真实验表明,该方法能有效地提高定位精度,能有效抑制具有较大量值的NLOS误差,是NLOS环境下一种有效的定位方法。更多还原

【Abstract】 To improve the accuracy of localization of mobile robot in indoor environment, an algorithm based on motion model is proposed in this paper. Forecasting of RSSI is proposed according to the motion model, and mean of the bias of prediction are applied to correct the polluted measurements. The presented method first proposes a way for NLOS identification and mitigation, then trilateration is replaced by computing the intersections of each two circles and a weighted average is applied to gain the position of the robot in which step-size is taken into account as the positioning range qualification, finally the extended Kalman filter is applied to gain the optimal estimation of localization. Effectiveness of the localization method is proved by simulation, in which the presented method gains an excellent performance especially when NLOS errors occur.更多还原