振动平滑蟋蟀定位系统中扩展卡尔曼滤波的无人机器人实时跟踪

Jae-Bong Yoo, Chan Young Park
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引用次数: 0

摘要

在传感器网络中,对移动节点跟踪的研究越来越多,但到目前为止,几乎所有关于移动设备跟踪的研究都是利用编码器、陀螺仪和加速度计等传感器来估计移动设备的移动距离。从这个角度来看,我们提出了验证跟踪实验的方法,通过将移动节点的位置映射到从网络摄像头获得的图像中,而无需任何额外的传感器。该方法有助于比较主动和被动结构下无人机器人跟踪的实验结果。为了消除无人机器人的电机对超声波传感器的干扰影响,我们在原有蟋蟀的基础上对振动平滑蟋蟀进行了改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Unmanned Robot Tracking with Extended Kalman Filter in the Vibration Smooth Cricket Location System
Researches about tracking mobile nodes are increasing in Sensor network but almost all studies about tracking a moving device up to recently should have been estimated their moving distance using encoder, gyro and accelerometer sensors and so on. In this point of view, we present methodology for verifying tracking experiments by mapping the position of a mobile node into images acquired from a Webcam without any additional sensors. The proposed method helps us compare experimental results of unmanned robot tracking in active and passive architecture. Vibration Smooth Cricket used in our experiments was modified from the original Cricket in order to remove unmanned robot's motor interference influences on ultrasonic sensors.
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