Nrobotic mobile robot navigation using traffic signs in unknown indoor environments

C. Purcaru, R. Precup, D. Iercan, L. Fedorovici, B. Dohangie, Florin Dragan
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引用次数: 3

Abstract

This paper proposes a navigation algorithm that allows mobile robots that participate in different missions to move in unknown environment. The algorithm uses data from the sonar or from the infrared sensors mounted on the robots and data from the video camera with which the robots are equipped. Using the video camera the robots will be able to detect and classify different traffic signs that can help the robots to arrive the target points safely and in a short time. The algorithm includes a convolutional neural network with six layers to classify the traffic signs. Several simulations were run on the nRobotic platform developed at the “Politehnica” University of Timisoara, Romania, to validate the new algorithm. The simulation scenarios illustrate attractive mechatronics applications concerning the behaviors of robots in unknown environments in the presence of multiple traffic signs.
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在未知室内环境中使用交通标志的非机器人移动机器人导航
本文提出了一种允许参与不同任务的移动机器人在未知环境中移动的导航算法。该算法使用安装在机器人上的声纳或红外传感器的数据,以及机器人配备的摄像机的数据。使用摄像机,机器人将能够检测和分类不同的交通标志,这可以帮助机器人在短时间内安全到达目标点。该算法采用六层卷积神经网络对交通标志进行分类。在罗马尼亚蒂米什瓦拉“波利特尼察”大学开发的nRobotic平台上进行了几次模拟,以验证新算法。仿真场景展示了具有吸引力的机电一体化应用,涉及机器人在未知环境中存在多个交通标志的行为。
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