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Multi-Sensor Person Following in Low-Visibility Scenarios

机译:低能见度场景中的多传感器人关注

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Person following with mobile robots has traditionally been an important research topic. It has been solved, in most cases, by the use of machine vision or laser rangefinders. In some special circumstances, such as a smoky environment, the use of optical sensors is not a good solution. This paper proposes and compares alternative sensors and methods to perform a person following in low visibility conditions, such as smoky environments in firefighting scenarios. The use of laser rangefinder and sonar sensors is proposed in combination with a vision system that can determine the amount of smoke in the environment. The smoke detection algorithm provides the robot with the ability to use a different combination of sensors to perform robot navigation and person following depending on the visibility in the environment.
机译:传统上,跟随机器人的人一直是重要的研究课题。在大多数情况下,已通过使用机器视觉或激光测距仪解决了该问题。在某些特殊情况下,例如烟雾弥漫的环境,使用光学传感器不是一个好的解决方案。本文提出并比较了在低能见度条件下(例如在消防场景中冒烟的环境中)执行人员跟踪的替代传感器和方法。建议将激光测距仪和声纳传感器与可以确定环境中烟雾量的视觉系统结合使用。烟雾检测算法使机器人能够根据环境的可见性使用不同的传感器组合来执行机器人导航和人员追踪。

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