首页> 美国卫生研究院文献>Frontiers in Neuroengineering >Mobile Robots for Localizing Gas Emission Sources on Landfill Sites: Is Bio-Inspiration the Way to Go?
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Mobile Robots for Localizing Gas Emission Sources on Landfill Sites: Is Bio-Inspiration the Way to Go?

机译:用于在垃圾填埋场定位气体排放源的移动机器人:生物灵感法走了吗?

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摘要

Roboticists often take inspiration from animals for designing sensors, actuators, or algorithms that control the behavior of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odor plume. In particular the task of tracking an odor plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behavior of moths, dung beetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro-drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behavior of animals, can be usefully “translated” into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically inspired algorithms.
机译:机器人专家经常从动物身上汲取灵感,设计出能够控制机器人行为的传感器,执行器或算法。动物具有超强的能力来激发生物灵感,以解决复杂的任务,例如识别和操纵物体,在崎uneven不平的地形上行走或导航到气味羽流的来源。特别是,使用生物学启发算法几乎完全解决了跟踪气味羽流直至其来源的任务,并且已经开发了机器人来模拟飞蛾,,甲虫或龙虾的行为。在本文中,我们认为仿生方法用于气源定位的用途有限,这主要是因为动物与先进的气敏移动机器人的传感和驱动能力根本不同。为了支持我们的主张,我们将可用于移动机器人的驱动和化学感应与飞蛾的相应功能进行了比较。我们进一步表征了在四个原型环境中使用三个不同的机器人平台(两个轮式机器人和一个飞行的微型无人机)获得的气流和化学传感器的测量结果,并证明了恒定和单向气流的假设是许多气源定位方法的基础,通常远非有效。该分析应有助于确定管理动物气源追踪行为的基本原理如何有效地“转化”为气源定位方法,从而充分考虑移动机器人的功能。我们还将描述参考应用程序的要求,使用移动机器人监控垃圾掩埋场的气体排放,并讨论基于统计的工程气源定位方法,以替代生物启发算法。

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