Grupo de Robótica, Universidad Rey Juan Carlos, Fuenlabrada, Spain.
Sensors (Basel). 2013 Jan 21;13(1):1268-99. doi: 10.3390/s130101268.
Cameras are one of the most relevant sensors in autonomous robots. However, two of their challenges are to extract useful information from captured images, and to manage the small field of view of regular cameras. This paper proposes implementing a dynamic visual memory to store the information gathered from a moving camera on board a robot, followed by an attention system to choose where to look with this mobile camera, and a visual localization algorithm that incorporates this visual memory. The visual memory is a collection of relevant task-oriented objects and 3D segments, and its scope is wider than the current camera field of view. The attention module takes into account the need to reobserve objects in the visual memory and the need to explore new areas. The visual memory is useful also in localization tasks, as it provides more information about robot surroundings than the current instantaneous image. This visual system is intended as underlying technology for service robot applications in real people's homes. Several experiments have been carried out, both with simulated and real Pioneer and Nao robots, to validate the system and each of its components in office scenarios.
相机是自主机器人中最重要的传感器之一。然而，它们面临的两个挑战是从捕获的图像中提取有用信息，以及管理常规相机的小视场。本文提出了一种动态视觉记忆，用于存储移动机器人上移动相机采集的信息，然后是一个注意系统，用于选择用移动相机观察的位置，以及一个视觉定位算法，该算法结合了这种视觉记忆。视觉记忆是一组相关的面向任务的对象和 3D 片段，其范围比当前相机的视场更宽。注意模块考虑了重新观察视觉记忆中对象的需求以及探索新区域的需求。视觉记忆在定位任务中也很有用，因为它提供了比当前瞬时图像更多的关于机器人周围环境的信息。该视觉系统旨在作为服务机器人在真实家庭中的应用的基础技术。已经进行了一些实验，包括使用模拟和真实的 Pioneer 和 Nao 机器人，以在办公场景中验证系统及其各个组件。
