An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments

Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown environment, wher...

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Autores principales:	Daniel Barry, Andreas Willig, Graeme Woodward
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	search and rescue wireless transmitters UAV drone Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/44124e7a8e104c579e065e1679f455aa
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id	oai:doaj.org-article:44124e7a8e104c579e065e1679f455aa
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spelling	oai:doaj.org-article:44124e7a8e104c579e065e1679f455aa2021-11-25T18:58:32ZAn Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments10.3390/s212276951424-8220https://doaj.org/article/44124e7a8e104c579e065e1679f455aa2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7695https://doaj.org/toc/1424-8220Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown environment, where the goal is to locate all transmitters in as short a time as possible. Existing solutions in the UAV search space typically search for a single target, assume a simple environment, assume target properties are known or have other unrealistic assumptions. We simulate large, complex environments with limited a priori information about the environment and transmitter properties. We propose a Bayesian search algorithm, Information Exploration Behaviour (IEB), that maximizes predicted information gain at each search step, incorporating information from multiple sensors whilst making minimal assumptions about the scenario. This search method is inspired by the information theory concept of empowerment. Our algorithm shows significant speed-up compared to baseline algorithms, being orders of magnitude faster than a random agent and 10 times faster than a lawnmower strategy, even in complex scenarios. The IEB agent is able to make use of received transmitter signals from unknown sources and incorporate both an exploration and search strategy.Daniel BarryAndreas WilligGraeme WoodwardMDPI AGarticlesearch and rescuewireless transmittersUAVdroneChemical technologyTP1-1185ENSensors, Vol 21, Iss 7695, p 7695 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	search and rescue wireless transmitters UAV drone Chemical technology TP1-1185
spellingShingle	search and rescue wireless transmitters UAV drone Chemical technology TP1-1185 Daniel Barry Andreas Willig Graeme Woodward An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
description	Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown environment, where the goal is to locate all transmitters in as short a time as possible. Existing solutions in the UAV search space typically search for a single target, assume a simple environment, assume target properties are known or have other unrealistic assumptions. We simulate large, complex environments with limited a priori information about the environment and transmitter properties. We propose a Bayesian search algorithm, Information Exploration Behaviour (IEB), that maximizes predicted information gain at each search step, incorporating information from multiple sensors whilst making minimal assumptions about the scenario. This search method is inspired by the information theory concept of empowerment. Our algorithm shows significant speed-up compared to baseline algorithms, being orders of magnitude faster than a random agent and 10 times faster than a lawnmower strategy, even in complex scenarios. The IEB agent is able to make use of received transmitter signals from unknown sources and incorporate both an exploration and search strategy.
format	article
author	Daniel Barry Andreas Willig Graeme Woodward
author_facet	Daniel Barry Andreas Willig Graeme Woodward
author_sort	Daniel Barry
title	An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
title_short	An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
title_full	An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
title_fullStr	An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
title_full_unstemmed	An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments
title_sort	information-motivated exploration agent to locate stationary persons with wireless transmitters in unknown environments
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/44124e7a8e104c579e065e1679f455aa
work_keys_str_mv	AT danielbarry aninformationmotivatedexplorationagenttolocatestationarypersonswithwirelesstransmittersinunknownenvironments AT andreaswillig aninformationmotivatedexplorationagenttolocatestationarypersonswithwirelesstransmittersinunknownenvironments AT graemewoodward aninformationmotivatedexplorationagenttolocatestationarypersonswithwirelesstransmittersinunknownenvironments AT danielbarry informationmotivatedexplorationagenttolocatestationarypersonswithwirelesstransmittersinunknownenvironments AT andreaswillig informationmotivatedexplorationagenttolocatestationarypersonswithwirelesstransmittersinunknownenvironments AT graemewoodward informationmotivatedexplorationagenttolocatestationarypersonswithwirelesstransmittersinunknownenvironments
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An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments

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