基于无线传感器网络的机器人定位跟踪研究

摘要

An improved algorithm based on wireless sensor network is proposed in order to solve robot localization problem. This algorithm introduces centroid algorithm into maximum likelihood estimation, and improves prediction accuracy of target location by calculating the centroid of several predicted data.Considering the relatively poor real time property of WSN system, extended (Caiman filter algorithm is adopted to track robot trajectory by combining WSN and DR system.The simulation shows that on condition of vary anchor nodes number and different raging error, the improved algorithm can achieve good results.The data fusion according to EKF algorithm further improves the accuracy of robot trajectory tracking.%针对基于无线传感器网络的机器人定位提出了一种分段极大似然质心算法.将质心法引入极大似然估计算法中,通过计算已预测结果的质心提高目标位置的预测精度.考虑到WSN系统的超声定位实时性较差,采用扩展卡尔曼滤波算法将WSN系统改进定位算法与机器人航位推算进行融合以跟踪机器人位姿,从而提高了定位精度和系统动态性能.仿真结果表明:在不同锚节点个数和不同测距误差条件下,分段极大似然质心算法均能取得良好的定位效果;采用扩展卡尔曼滤波算法的数据融合,进一步提高了机器人轨迹跟踪的精度.