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Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)

Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem in mobile robotics....

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Detalles Bibliográficos
Autores principales: Tang, Hong, Li, Liangzhi, Xiao, Nanfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336121/
https://www.ncbi.nlm.nih.gov/pubmed/28218649
http://dx.doi.org/10.3390/s17020393
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author Tang, Hong
Li, Liangzhi
Xiao, Nanfeng
author_facet Tang, Hong
Li, Liangzhi
Xiao, Nanfeng
author_sort Tang, Hong
collection PubMed
description Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem in mobile robotics. However, traditional methods are not suited for robotic sensors, because of their low efficiency, instability, and non-smooth-generated paths. This paper adopts an optimizing function to generate several intermediate points and regress these discrete points to a quintic polynomial which can output a smooth trajectory for the robotic sensor. Simulations demonstrate that our approach is robust and efficient, and can be well applied in the CPSS field.
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spelling pubmed-53361212017-03-16 Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS) Tang, Hong Li, Liangzhi Xiao, Nanfeng Sensors (Basel) Article Although many researchers have begun to study the area of Cyber Physical Social Sensing (CPSS), few are focused on robotic sensors. We successfully utilize robots in CPSS, and propose a sensor trajectory planning method in this paper. Trajectory planning is a fundamental problem in mobile robotics. However, traditional methods are not suited for robotic sensors, because of their low efficiency, instability, and non-smooth-generated paths. This paper adopts an optimizing function to generate several intermediate points and regress these discrete points to a quintic polynomial which can output a smooth trajectory for the robotic sensor. Simulations demonstrate that our approach is robust and efficient, and can be well applied in the CPSS field. MDPI 2017-02-17 /pmc/articles/PMC5336121/ /pubmed/28218649 http://dx.doi.org/10.3390/s17020393 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tang, Hong
Li, Liangzhi
Xiao, Nanfeng
Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
title Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
title_full Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
title_fullStr Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
title_full_unstemmed Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
title_short Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS)
title_sort smooth sensor motion planning for robotic cyber physical social sensing (cpss)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336121/
https://www.ncbi.nlm.nih.gov/pubmed/28218649
http://dx.doi.org/10.3390/s17020393
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AT liliangzhi smoothsensormotionplanningforroboticcyberphysicalsocialsensingcpss
AT xiaonanfeng smoothsensormotionplanningforroboticcyberphysicalsocialsensingcpss