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Image-based memory for robot navigation using properties of omnidirectional images

机译:基于图像的内存,用于使用全向图像属性进行机器人导航

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This paper proposes a new technique for vision-based robot navigation. The basic framework is to localise the robot by comparing images taken at its current location with reference images stored in its memory. In this work, the only sensor mounted on the robot is an omnidirectional camera. The Fourier components of the omnidirectional image provide a signature for the views acquired by the robot and can be used to simplify the solution to the robot navigation problem. The proposed system can calculate the robot position with variable accuracy ('hierarchical localisation') saving computational time when the robot does not need a precise localisation (e.g. when it is travelling through a clear space). In addition, the system is able to self-organise its visual memory of the environment. The self-organisation of visual memory is essential to realise a fully autonomous robot that is able to navigate in an unexplored environment. Experimental evidence of the robustness of this system is given in unmodified office environments.
机译:本文提出了一种基于视觉的机器人导航新技术。基本框架是通过比较机器人当前位置拍摄的图像与存储在其内存中的参考图像来定位机器人。在这项工作中,安装在机器人上的唯一传感器是全向摄像机。全向图像的傅立叶分量为机器人获取的视图提供签名,可用于简化机器人导航问题的解决方案。所提出的系统可以以可变的精度(“分层定位”)来计算机器人的位置,从而在机器人不需要精确的定位时(例如,当它穿越空白空间时)节省了计算时间。另外,该系统能够自组织其对环境的视觉记忆。视觉记忆的自组织对于实现能够在未开发环境中导航的完全自主的机器人至关重要。在未经修改的办公环境中提供了该系统的鲁棒性的实验证据。

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