基于一致性Unsented卡尔曼滤波的多机器人定位-《计算机技术与发展》

文章信息/Info

Title:: Localization for Multi-Robot Based on Unsented Kalman-Consensus Filter

摘要:: 主要研究了多机器人编队过程中机器人的定位问题。在编队过程中机器人仅利用通过场地上方的摄像头捕获的图像得到自身的位置容易受干扰导致定位不准。利用队列中某个机器人观测到另外一个或几个机器人时，用相对观测信息和自身的位置以及附近被观测机器人的位置估计来更新一致性Unsented卡尔曼滤波算法中的状态估计。最后通过实验来对比未滤波前定位精度和分别采用Unsented卡尔曼滤波算法和一致性Unsented卡尔曼滤波算法定位精度，实验结果表明一致性Unsented卡尔曼滤波算法能够有效地提高定位的精度

Abstract:: The problem of robot localization in the process of multi-robot formation was studied in this paper. The position of robot obtained from the image captured by the camera on the ceiling was inaccurate. When one robot was observed by the other robot, use the relative observation, its own position and estimation of the observed robots＇ position to update the state estimation in the unsented Kalman -consensus filter. The experiment results show that the unsented Kalman-consensus filter method is more effective in dealing with the localization of robot than the unsented Kalman filter method