小型移动机器人的环境感知行为

D. Withey, Katlego Mogokonyane, Mayur Tikam, Ross Holder, Mahalingam Veeraragoo, Mxolisi Gambushe
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引用次数: 0

摘要

移动GPU计算和实时物体识别的同步进步现在使机器能够根据环境中感兴趣的物体的检测做出决策并采取行动。本文描述了一种移动机器人系统的实现,该系统将自主探索和地图绘制能力与基于运行在移动GPU上的深度神经网络的实时目标识别方法相结合。该系统能够检测到感兴趣的物体,然后采取实时行动与物体进行交互,在这种情况下,通过移动从多个角度获取物体的检查式图像。这个机器人系统很小,设备齐全,靠电池供电。该系统显示了具有上下文感知的机器人系统的发展潜力,允许高级自治。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Context-Aware Action with a Small Mobile Robot
Simultaneous advances in mobile GPU computing and real-time object recognition now enable machines to make decisions and take actions based on the detection of objects of interest in the environment. An implementation of a mobile robot system that combines autonomous exploration and mapping capabilities with a real-time object recognition method based on a deep neural network running on a mobile GPU, is described. The system is able to detect objects of interest and then take real-time actions to interact with the objects, in this case, by moving to acquire inspection-style images of the object, from multiple angles. The robot system is small, self-contained and runs on battery power. The system shows the potential for the development of robotic systems with context awareness, permitting advanced autonomy.
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