CLC number: TP242.6
On-line Access: 2023-07-03
Received: 2022-05-14
Revision Accepted: 2022-11-15
Crosschecked: 2023-07-03
Cited: 0
Clicked: 1091
Citations: Bibtex RefMan EndNote GB/T7714
Gengyu GE, Yi ZHANG, Wei WANG, Lihe HU, Yang WANG, Qin JIANG. Visual-feature-assisted mobile robot localization in a long corridor environment[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2200208 @article{title="Visual-feature-assisted mobile robot localization in a long corridor environment", %0 Journal Article TY - JOUR
长走廊环境下视觉特征辅助的移动机器人定位研究1重庆邮电大学计算机科学与技术学院,中国重庆市,400065 2重庆邮电大学先进制造工程学院,中国重庆市,400065 3遵义师范学院信息工程学院,中国遵义市,563006 摘要:定位在移动机器人导航系统中起着至关重要的作用,是自主移动的基本能力。在室内环境中,当前主流的定位方案使用2D激光雷达,利用即时定位和建图(SLAM)技术来构建占据栅格地图;然后,基于已知的地图来定位。然而,此类方案仅在具有显著几何特征的区域有效。对于重复、对称或类似结构的区域,例如长走廊,常规粒子过滤方法将失效。为解决这一问题,本文提出一种从粗到细的模式,该模式使用视觉特征辅助长走廊中的移动机器人定位。首先,移动机器人被远程控制,沿着中线从起始位置移动到终点。在移动过程中,使用基于激光的SLAM方法建图。同时,根据关键帧选择策略创建关键帧图像组成的视觉地图。关键帧通过时间戳与机器人的姿势相关联。其次,基于提取的激光扫描距离特征,提出一种移动策略,确定初始粗略位置。这对于移动机器人来说至关重要,因为它给出了机器人需要移动到哪里才能调整姿势的指令。然后,移动机器人根据移动策略以适当的视角捕捉图像,并将其与图像地图进行匹配,以获得粗略的定位。最后,提出一种改进的粒子滤波方法来实现精细定位。实验结果表明,该方法对全局定位是有效和鲁棒的。定位成功率达98.8%,平均移动距离仅0.31米。此外,当移动机器人被绑架到走廊中的另一个位置时,该方法依然有效。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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