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A Visual SLAM System on Mobile Robot Supporting Localization Services to Visually Impaired People

机译:支持视觉障碍者本地化服务的移动机器人上的Visual SLAM系统

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This paper describes a Visual SLAM system developed on a mobile robot in order to support localization services to visually impaired people. The proposed system aims to provide services in small or mid-scale environments such as inside a building or campus of school where conventional positioning data such as GPS, WIFI signals are often not available. Toward this end, we adapt and improve existing vision-based techniques in order to handle issues in the indoor environments. We firstly design an image acquisition system to collect visual data. On one hand, a robust visual odometry method is adjusted to precisely create the routes in the environment. On the other hand, we utilize the Fast-Appearance Based Mapping algorithm that is may be the most successful for matching places in large scenarios. In order to better estimate robot's location, we utilize a Kalman Filter that combines the matching results of current observation and the estimation of robot states based on its kinematic model. The experimental results confirmed that the proposed system is feasible to navigate the visually impaired people in the indoor environments.
机译:本文介绍了在移动机器人上开发的Visual SLAM系统,以支持视障人士的本地化服务。拟议中的系统旨在在小型或中型环境中提供服务,例如在建筑物或学校校园内,而传统定位数据(例如GPS,WIFI信号)通常不可用。为此,我们调整并改进了现有的基于视觉的技术,以处理室内环境中的问题。我们首先设计一个图像采集系统来收集视觉数据。一方面,调整了鲁棒的视觉测距法,以精确地在环境中创建路线。另一方面,我们利用了基于快速外观的映射算法,该算法对于大型场景中的位置匹配而言可能是最成功的。为了更好地估计机器人的位置,我们利用卡尔曼滤波器将当前观测值的匹配结果与基于其运动学模型的机器人状态估计相结合。实验结果证实了所提出的系统在导航室内视觉障碍者方面是可行的。

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