首页> 外文会议>International Conference on Information Fusion >A Particle Filter Localisation System for Indoor Track Cycling Using an Intrinsic Coordinate Model
【24h】

A Particle Filter Localisation System for Indoor Track Cycling Using an Intrinsic Coordinate Model

机译:基于本征坐标模型的室内轨道自行车颗粒过滤器定位系统

获取原文
获取外文期刊封面目录资料

摘要

In this paper we address the challenging task of tracking a fast-moving bicycle, in the indoor velodrome environment, using inertial sensors and infrequent position measurements. Since the inertial sensors are physically in the intrinsic frame of the bike, we adopt an intrinsic frame dynamic model for the motion, based on curvilinear dynamical models for manoeuvring objects. We show that the combination of inertial measurements with the intrinsic dynamic model leads to linear equations, which may be incorporated effectively into particle filtering schemes. Position measurements are provided through timing measurements on the track from a camera-based system and these are fused with the inertial measurements using a particle filter weighting scheme. The proposed methods are evaluated on synthesised cycling datasets based on real motion trajectories, showing their potential accuracy, and then real data experiments are reported.
机译:在本文中,我们解决了使用惯性传感器和不频繁的位置测量在室内赛车场环境中跟踪快速行驶的自行车这一艰巨的任务。由于惯性传感器物理上位于自行车的固有框架中,因此我们基于运动对象的曲线动力学模型为运动采用固有框架动力学模型。我们表明,惯性测量与内在动力学模型的结合导致了线性方程,可以将其有效地纳入粒子滤波方案中。位置测量是通过基于摄像头的系统通过轨道上的定时测量提供的,并且使用粒子滤波器加权方案将这些测量与惯性测量相融合。在基于真实运动轨迹的合成自行车数据集上对提出的方法进行了评估,显示了其潜在的准确性,然后报告了真实的数据实验。

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