Demo: Measuring Distance Traveled by an Object using WiFi-CSI and IMU Fusion

Raghav H. Venkatnarayan, Muhammad Shahzad
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引用次数: 3

Abstract

Accurately measuring the distance traveled by an object or odometry, in indoor environments is important in many applications such as video-game controller tracking or robot route guidance. While the distance traveled by an object can be simply measured using an accelerometer, it is wellknown that distances measured with accelerometers suffer from large drift errors. In this paper, we demonstrate WIO, a WiFiassisted Inertial Odometry technique that uses WiFi signals as an auxiliary source of information to correct such drift errors. The key intuition behind WIO is that, among multiple paths of a transmitted WiFi signal that arrive at a moving object equipped with a WiFi receiver, WIO can isolate the path that is most parallel to the object’s direction of motion and use the change in the length of that path as an estimate of the traversed distance. WIO then fuses this distance estimate with the distance measured from an accelerometer on-board the object to correct drift errors. We implement WIO using commodity devices, and evaluate it on a robot car. Our results demonstrate an average error of just 4.37% in estimating the distance traversed by the car.
演示:使用WiFi-CSI和IMU融合测量物体行进的距离
在室内环境中,精确测量物体或里程计所走过的距离在许多应用中都很重要,例如视频游戏控制器跟踪或机器人路线引导。虽然物体移动的距离可以简单地用加速度计测量,但众所周知,用加速度计测量的距离有很大的漂移误差。在本文中,我们演示了WIO,一种WiFi辅助惯性里程计技术,它使用WiFi信号作为辅助信息源来纠正这种漂移误差。WIO背后的关键直觉是,在传输的WiFi信号到达装有WiFi接收器的运动物体的多条路径中,WIO可以隔离出与物体运动方向最平行的路径,并使用该路径长度的变化来估计穿过的距离。然后,WIO将这个距离估计与机载加速度计测量的距离融合,以纠正漂移误差。我们使用商品设备实现了WIO,并在机器人汽车上进行了评估。我们的结果表明,在估计汽车穿过的距离时,平均误差仅为4.37%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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