首页> 外文会议>IEEE International Conference on Signal Processing, Communications and Computing >Error modeling of various sensors for robotics application using Allan Variance technique
【24h】

Error modeling of various sensors for robotics application using Allan Variance technique

机译:Allan方差技术的机器人应用程序各种传感器的错误建模

获取原文

摘要

Present day mobile robots are meant for very precise applications. For very precise applications of mobile robots, accurate estimation of inertial parameters depends upon the accuracy of mathematical model & as well as accuracy (error characteristics) of the individual sensor measurements. Multiple sensors add redundancies to the system as well as it helps to estimate the system states accurately through judicious fusion. As sensor measurements itself are prone to various types of noises, the detail error modeling is very essential for estimation of appropriate signals from the noisy sensor data. The essence of the error modeling is to understand & characterize the different types of noises present in the measured. This paper illustrates the characterization and identification of noises present in the Encoder (Model: Maxon HEDL-5540) & Inertial navigation system (Model: Crossbow NAV440) measurements using Allan Variance technique.
机译:目前的移动机器人适用于非常精确的应用。对于移动机器人的非常精确的应用,准确估计惯性参数取决于数学模型的准确性,以及各个传感器测量的准确性(误差特性)。多个传感器向系统添加冗余以及有助于通过明智融合准确地估计系统状态。由于传感器测量本身容易出现各种类型的噪声,但细节误差建模对于估计来自噪声传感器数据的适当信号非常重要。错误建模的本质是理解和表征测量中存在的不同类型的噪声。本文说明了使用Allan方差技术的编码器(型号:Maxon HEDL-5540)和惯性导航系统(型号:弩NAV440)测量中存在的噪声的表征和识别。

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