首页> 外文会议>Youth Academic Annual Conference of Chinese Association of Automation >Research on UWB/QR Sensor Fusion Location Algorithm based on UKF and FIS
【24h】

Research on UWB/QR Sensor Fusion Location Algorithm based on UKF and FIS

机译:基于UKF和FIS的UWB / QR传感器融合定位算法研究

获取原文

摘要

Demanding for precision and flexibility of Automatic Guided Vehicle is critical with the rapid development of logistics automation and factory automation, a low-cost sensor fusion positioning method is proposed in this paper. The sensors used in this paper are Ultra Wide Band (UWB), a Gyroscope, Encoders, and the Camera (QR), and a more accurate pose can be obtained by the unscented Kalman filter (UKF). At the same time, the fuzzy inference system (FIS) is used to output the noise of UKF. To demonstrate the performance of the proposed method, we use the simulated sensor data signal and carry out several simulations under different working conditions. Finally, the simulation demonstrates that the proposed method can effectively overcome the low positioning accuracy of a single sensor and the UWB/QR sensor fusion location algorithm can achieve accurate positioning information.
机译:对自动引导车辆的精度和灵活性苛刻,随着物流自动化和工厂自动化的快速发展至关重要,本文提出了一种低成本的传感器融合定位方法。本文中使用的传感器是超宽带(UWB),陀螺仪,编码器和相机(QR),并且可以通过Unscented Kalman滤波器(UKF)获得更准确的姿势。同时,模糊推理系统(FIS)用于输出UKF的噪声。为了证明所提出的方法的性能,我们使用模拟传感器数据信号并在不同的工作条件下进行多个模拟。最后,模拟表明,所提出的方法可以有效地克服单个传感器的低定位精度,并且UWB / QR传感器融合位置算法可以实现准确的定位信息。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号