Chemical Source Searching by Controlling a Wheeled Mobile Robot to Follow an Online Planned Route in Outdoor Field Environments.

chemical-patch path (C-PP) chemical-source tracing outdoor field environments search-route planning wheeled mobile robot

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
21 Jan 2019
Historique:
received: 13 12 2018
revised: 11 01 2019
accepted: 17 01 2019
entrez: 24 1 2019
pubmed: 24 1 2019
medline: 24 1 2019
Statut: epublish

Résumé

In this paper, we present an estimation-based route planning (ERP) method for chemical source searching using a wheeled mobile robot and validate its effectiveness with outdoor field experiments. The ERP method plans a dynamic route for the robot to follow to search for a chemical source according to time-varying wind and an estimated chemical-patch path (C-PP), where C-PP is the historical trajectory of a chemical patch detected by the robot, and normally different from the chemical plume formed by the spatial distribution of all chemical patches previously released from the source. Owing to the limitations of normal gas sensors and actuation capability of ground mobile robots, it is quite hard for a single robot to directly trace the intermittent and rapidly swinging chemical plume resulting from the frequent and random changes of wind speed and direction in outdoor field environments. In these circumstances, tracking the C-PP originating from the chemical source back could help the robot approach the source. The proposed ERP method was tested in two different outdoor fields using a wheeled mobile robot. Experimental results indicate that the robot adapts to the time-varying airflow condition, arriving at the chemical source with an average success rate and approaching effectiveness of about 90% and 0.4~0.6, respectively.

Identifiants

pubmed: 30669633
pii: s19020426
doi: 10.3390/s19020426
pmc: PMC6359492
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : the National Natural Science Foundation of China
ID : 61573253, 61603270
Organisme : National Key R&D Program of China
ID : 2017YFC0306200
Organisme : Tianjin Natural Science Foundation
ID : 16JCYBJC16400

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Auteurs

Ji-Gong Li (JG)

Tianjin Key Laboratory of Information Sensing and Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China. charles75@163.com.
Institute of Robotics and Autonomous Systems, Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China. charles75@163.com.

Meng-Li Cao (ML)

Institute of Robotics and Autonomous Systems, Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China. menglicao@tju.edu.cn.
Logistics Engineering College, Shanghai Marinetime University, Shanghai 201306, China. menglicao@tju.edu.cn.

Qing-Hao Meng (QH)

Institute of Robotics and Autonomous Systems, Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China. qh_meng@tju.edu.cn.

Classifications MeSH