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Empirical Study on Premises Monitoring Algorithm Implementation in Mobile Robotic System

机译:移动机器人系统中房地监测算法实现的实证研究

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Mobile robotic systems have gained major attention from the whole global community for their unique features and ability to automate routine processes. Such systems can be implemented to optimize the monitoring process in dynamic dangerous or unknown environments. In this paper, we provide the algorithm for premises monitoring by a group of custom mobile robots. The main legitimate agents’ task is to detect all intruder agents, located in the premise. The proposed approach is based on the optimization task, which requires legitimate agents to perform monitoring according to the optimization criteria. To test the proposed algorithm, we designed a physical testing ground, which includes models of the premises with rooms and a narrow corridor, legitimate agents, and an intruder. To assess the algorithm implementation effectiveness on mobile robots to detect the intruder, we compared it using two types of sensors: on-board camera with the computer vision application, and ultrasonic range finders. Experiment results showed that despite classification errors, occurred in the monitoring process, computer vision application provided faster and flexible detection than using ultrasonic range finders.
机译:移动机器人系统已经获得了重大的注意力从整个国际社会为他们的独特的功能和自动化日常流程的能力。这样的系统可被实现以优化监视过程中动态危险的或未知的环境。在本文中,我们提供了场所由一组自定义的移动机器人的监测算法。主要的合法代理商的任务是检测所有入侵者代理人,位于前提。所提出的方法是基于优化的任务,需要合法代理商来执行根据优化标准监控。为了测试算法,我们设计了一个物理试验场,其中包括与房间和一个狭窄的走廊,合法代理商,以及入侵者处所的车型。为了评估在移动机器人的算法实现的有效性,以检测入侵者,我们比较它使用两种类型的传感器:车载摄像机与计算机视觉应用,和超声波测距仪。实验结果显示,尽管分类错误,发生在监控过程中,计算机视觉应用提供快速,灵活的检测比使用超声波测距仪。

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