Visual robot navigation

视觉机器人导航

• 批准号: 327491-2006
• 负责人: Vardy, Andrew
• 金额: $ 1.09万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=365230
• 关键词: Visual; robot; navigation

The objective of this research program is to develop methods for robots to navigate in unstructured environments.  Unstructured environments are those which have not been specifically designed for robot operation.  The approach taken here is partially inspired by biological models.  The current view of navigation in insects such as bees, ants, and wasps is that these insects capture "snapshot images" throughout their environment.  They then use a procedure called visual homing to move between snapshot positions.  This research will apply a similar methodology to robots. Robot navigation is a difficult problem for two fundamental reasons:  (1) Using odometric information to estimate position incurs a cumulative error.  In other words, the further a robot travels, the more unsure it becomes of its position.  (2) Places that have the same appearance cannot be distinguished.  Interestingly, most existing methods can address one of the above difficulties, but seldom both. This research program will utilize visual homing to allow a robot to travel between places where it had previously captured snapshot images.  We will begin with an existing model for navigation based on homing, and incorporate additional insights so as to resolve the problems described above.  The desired end product of this research will be a set of methods which allow a robot to travel robustly between known places.  The challenge is to make these methods truly robust so that available visual cues are utilized while noise is ignored. The applications for robustly navigating robots are both numerous and diverse.  Some example applications are autonomous driving, planetary exploration, search and rescue, surveillance, remote sensing, and household cleaning.

该研究计划的目标是开发机器人在非结构化环境中导航的方法。非结构化环境是指那些没有专门为机器人操作设计的环境。这里采用的方法部分受到生物模型的启发。目前对蜜蜂，蚂蚁，和黄蜂的不同之处在于，这些昆虫在整个环境中捕捉“快照图像”。然后它们使用一种称为视觉寻的程序在快照位置之间移动。这项研究将把类似的方法应用于机器人。机器人导航是一个困难的问题，有两个基本原因：（1）使用里程信息来估计位置会产生累积误差。换句话说，机器人走得越远，它就越不确定自己的位置。（2）具有相同外观的地方无法区分。有趣的是，大多数现有的方法可以解决上述困难之一，但很少同时解决这两个问题。这项研究计划将利用视觉归航，让机器人之间的地方，它以前捕捉快照图像旅行。我们将开始与现有的导航模型的基础上归航，并结合额外的见解，以解决上述问题。这项研究的预期最终产品将是一套方法，使机器人能够在已知地点之间稳健地旅行。挑战是以使这些方法真正鲁棒，从而在忽略噪声的同时利用可用的视觉线索。鲁棒导航机器人的应用范围非常广泛，例如自动驾驶、行星探索、搜索和救援、监视、遥感和家庭清洁等。