A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.

We introduce a unified simulation framework that generates natural sensing environments and produces biosonar echoes under various sensing scenarios. This framework produces rich sensory data with environmental information completely known, thus can be used for the training of robotic algorithms for...

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Main Authors: M Hassan Tanveer, Xiaowei Wu, Antony Thomas, Chen Ming, Rolf Müller, Pratap Tokekar, Hongxiao Zhu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0241443
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author M Hassan Tanveer
Xiaowei Wu
Antony Thomas
Chen Ming
Rolf Müller
Pratap Tokekar
Hongxiao Zhu
author_facet M Hassan Tanveer
Xiaowei Wu
Antony Thomas
Chen Ming
Rolf Müller
Pratap Tokekar
Hongxiao Zhu
author_sort M Hassan Tanveer
collection DOAJ
description We introduce a unified simulation framework that generates natural sensing environments and produces biosonar echoes under various sensing scenarios. This framework produces rich sensory data with environmental information completely known, thus can be used for the training of robotic algorithms for biosonar-based Unmanned Aerial Vehicles. The simulated environment consists of random trees with full geometry of the tree foliage. To simulate a single tree, we adopt the Lindenmayer system to generate the initial branching pattern and integrate that with the available measurements of the 3D computer-aided design object files to create natural-looking branches, sub-branches, and leaves. A forest is formed by simulating trees at random locations generated by using an inhomogeneous Poisson process. While our simulated environments can be generally used for testing other sensors and training robotic algorithms, in this study we focus on testing bat-inspired Unmanned Aerial Vehicles that recreate bat's flying behavior through biosonar sensors. To this end, we also introduce an foliage echo simulator that produces biosonar echoes while mimicking bat's biosonar system. We demonstrate the application of the proposed simulation framework by generating real-world scenarios with multiple trees and computing the resulting impulse responses under static or dynamic motions of an Unmanned Aerial Vehicle.
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spelling doaj.art-511c843cf26d4244bd72b35f614e80ab2022-12-21T18:40:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-011511e024144310.1371/journal.pone.0241443A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.M Hassan TanveerXiaowei WuAntony ThomasChen MingRolf MüllerPratap TokekarHongxiao ZhuWe introduce a unified simulation framework that generates natural sensing environments and produces biosonar echoes under various sensing scenarios. This framework produces rich sensory data with environmental information completely known, thus can be used for the training of robotic algorithms for biosonar-based Unmanned Aerial Vehicles. The simulated environment consists of random trees with full geometry of the tree foliage. To simulate a single tree, we adopt the Lindenmayer system to generate the initial branching pattern and integrate that with the available measurements of the 3D computer-aided design object files to create natural-looking branches, sub-branches, and leaves. A forest is formed by simulating trees at random locations generated by using an inhomogeneous Poisson process. While our simulated environments can be generally used for testing other sensors and training robotic algorithms, in this study we focus on testing bat-inspired Unmanned Aerial Vehicles that recreate bat's flying behavior through biosonar sensors. To this end, we also introduce an foliage echo simulator that produces biosonar echoes while mimicking bat's biosonar system. We demonstrate the application of the proposed simulation framework by generating real-world scenarios with multiple trees and computing the resulting impulse responses under static or dynamic motions of an Unmanned Aerial Vehicle.https://doi.org/10.1371/journal.pone.0241443
spellingShingle M Hassan Tanveer
Xiaowei Wu
Antony Thomas
Chen Ming
Rolf Müller
Pratap Tokekar
Hongxiao Zhu
A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.
PLoS ONE
title A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.
title_full A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.
title_fullStr A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.
title_full_unstemmed A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.
title_short A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.
title_sort simulation framework for bio inspired sonar sensing with unmanned aerial vehicles
url https://doi.org/10.1371/journal.pone.0241443
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