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引用次数: 1

摘要

机器人视觉是一个跨学科领域,研究如何使机器人从数字图像或视频中获得高层次的理解。在像素水平上理解图像通常不能为决策和采取行动提供足够的信息。在这种情况下,需要描述图像的高级语义信息。这有助于机器人完成需要视觉理解的复杂任务。为了让机器人增加价值,它们需要在不同的环境中足够有效地执行任务。尽管在机器人视觉方面取得了许多令人印象深刻的进步,但机器人仍然缺乏在复杂环境中像人类一样工作的能力。重要的是,这包括能够解释和理解感知世界的复杂性。机器人视觉依赖于计算机视觉和机器学习的思想。在本文中,我们概述了这些学科的进展以及它们如何对机器人视觉做出贡献。
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An overview of robot vision
Robot vision is an interdisciplinary field that deals with how robots can be made to gain high-level understanding from digital images or videos. Understanding an image at the pixel level often does not provide enough information for decision making and action taking. In this case, higher level semantic information that describes the image is required. This helps the robot to accomplish complex tasks that require visual understanding.For robots to add value they need to be sufficiently effective at executing tasks in different settings. Despite many impressive advances in robot vision, robots still lack the ability to function as humans do in complex environments. Importantly, this includes being able to interpret and understand the perceptual complexities of the world.Robot vision is dependant on ideas from both computer vision and machine learning. In this paper we provide a overview of the advances in these disciplines and how they contribute to robot vision.
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