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用于降低室内机器人定位与导航中垂直高度敏感度的无焦光流传感器。

Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

作者信息

Yi Dong-Hoon, Lee Tae-Jae, Cho Dong-Il Dan

机构信息

Department of Electrical and Computer Engineering, Automation and Systems Research Institute (ASRI), Seoul National University, Seoul 151-742, Korea.

Inter-University Semiconductor Research Center (ISRC), Seoul National University, Seoul 151-742, Korea.

出版信息

Sensors (Basel). 2015 May 13;15(5):11208-21. doi: 10.3390/s150511208.

Abstract

This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

摘要

本文介绍了一种用于室内机器人导航里程计估计的新型无焦光流传感器(OFS)系统。计算机光学鼠标中使用的OFS已被应用于移动机器人,因为它不受车轮打滑的影响。当在不平坦表面上行驶的移动机器人估计移动距离时,垂直高度变化被认为是系统误差的主要因素。我们提出了一种使用无焦(无限有效焦距)系统来减轻这种误差的方法。我们在地毯和其他三种材料的线性导轨上进行了实验,传感器高度在30至50毫米之间变化,移动距离为80厘米。相同的实验重复了10次。对于所提出的无焦OFS模块,传感器高度每变化1毫米会导致0.1%的系统误差;相比之下,传统固定焦距OFS模块的误差为14.7%。最后,将所提出的无焦OFS模块安装在移动机器人上,并在地毯上进行了10次1米距离的测试。平均距离估计误差和标准差分别为0.02%和17.6%,而传统OFS模块的平均距离估计误差和标准差分别为4.09%和25.7%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb0/4481980/c144d5a05e31/sensors-15-11208-g002.jpg

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