Visual object recognition for robot tasks in real-life scenarios

Ester Martínez-Martín, A. P. Pobil
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引用次数: 5

Abstract

On the way to autonomous robotic systems, key issues are object detection and recognition. In this paper, we aim at robustly detecting and recognizing different objects in real-life scenarios from a visual input when robot manipulation is the goal task. For that, and based on the human vision system performance, the system computes object's colour, motion and shape cues and combines them in a probabilistic manner to accurately achieve object identification and recognition task. More-over, a Graphical Processing Unit (GPU) is used to fulfill the requirement for real-time visual data processing. In addition, it has been implemented and tested on a robotic platform.
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真实场景中机器人任务的视觉对象识别
在自主机器人系统的道路上,关键问题是物体检测和识别。在本文中,我们的目标是在机器人操作为目标任务的情况下,从视觉输入中鲁棒地检测和识别现实场景中的不同物体。为此,该系统以人类视觉系统的表现为基础,计算物体的颜色、运动和形状线索,并以概率的方式将它们组合起来,准确地完成物体的识别任务。并采用图形处理器(GPU)实现实时可视化数据处理。此外,它已经在机器人平台上实现和测试。
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