传感器融合在多机器人合作定位中的应用

Application of Sensor Fusion in Multi-robot Cooperative Localization

机器人的定位技术是进行机器人环境探索、协调运动研究的前提,从信息融合的思想出发,提出了一种融合多传感器信息的合作定位技术。首先,对两轮机器人的基本运动形式进行建模,并针对超声波传感器建立了机器人之间的相对观测方程。然后,分别对机器人的内、外部传感器进行滤波和第一级融合,得到自身位姿和相对观测信息。最后,利用扩展卡尔曼滤波(EKF)融合机器人的自身位姿和观测信息,实现多机器人的合作定位。实验结果表明,本合作定位能够使机器人之间互为路标,消除码盘定位的累积误差,有效地提高机器人定位精度。

Robot localization is the premise of other robot research ,such as environment explore and motion coordination. Inspired by information fusion, a novel muhi-robot cooperative localization technology is presented,which fuses the robot＇ s multiple sensor data. First,the basic motion form of the two-wheel robot was modeled, and the relative observing formu- la was built aiming at the ultrasonic sensor. Then filtering and first-level fusion were applied to robots proprioceptive and exteroceptive sensors respectively,by which obtained the robot＇s proprioceptive location data and relative observing data. Finally, the robot＇s proprioceptive location data and observing data were fused by extension kalman filter （EKF）,and the multi-robot cooperative localization was implemented. Experiment result demonstrates this cooperative localization technology can get the robots to form landmarks for each other,eliminate the accumulate error from encoder,and improve the robot localization accuracy efficiently.