relation: https://khub.utp.edu.my/scholars/19405/
title: Mobile Robot Gas Source Localization Using SLAM-GDM with a Graphene-Based Gas Sensor
creator: Norzam, W.A.S.
creator: Hawari, H.F.
creator: Kamarudin, K.
creator: Juffry, Z.H.M.
creator: Hussein, N.A.A.
creator: Gupta, M.
creator: Abdullah, A.N.
description: Mobile olfaction is one of the applications of mobile robots. Metal oxide sensors (MOX) are mobile robots� most popular gas sensors. However, the sensor has drawbacks, such as high-power consumption, high operating temperature, and long recovery time. This research compares a reduced graphene oxide (RGO) sensor with the traditionally used MOX in a mobile robot. The method uses a map created from simultaneous localization and mapping (SLAM) combined with gas distribution mapping (GDM) to draw the gas distribution in the map and locate the gas source. RGO and MOX are tested in the lab for their response to 100 and 300 ppm ethanol. Both sensors� response and recovery times show that RGO resulted in 56 and 54 faster response times, with 33 and 57 shorter recovery times than MOX. In the experiment, one gas source, 95 ethanol solution, is placed in the lab, and the mobile robot runs through the map in 7 min and 12 min after the source is set, with five repetitions. The results show the average distance error of the predicted source from the actual location was 19.52 cm and 30.28 cm using MOX and 25.24 cm and 30.60 cm using the RGO gas sensor for the 7th and 12th min trials, respectively. The errors show that the predicted gas source location based on MOX is 1.0 (12th min), much closer to the actual site than that predicted with RGO. However, RGO also shows a larger gas sensing area than MOX by 0.35�8.33 based on the binary image of the SLAM-GDM map, which indicates that RGO is much more sensitive than MOX in the trial run. Regarding power consumption, RGO consumes an average of 294.605 mW, 56.33 less than MOX, with an average consumption of 674.565 mW. The experiment shows that RGO can perform as well as MOX in mobile olfaction applications but with lower power consumption and operating temperature. © 2022 by the authors.
date: 2023
type: Article
type: PeerReviewed
identifier:   Norzam, W.A.S. and Hawari, H.F. and Kamarudin, K. and Juffry, Z.H.M. and Hussein, N.A.A. and Gupta, M. and Abdullah, A.N.  (2023) Mobile Robot Gas Source Localization Using SLAM-GDM with a Graphene-Based Gas Sensor.  Electronics (Switzerland), 12 (1).       
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145907203&doi=10.3390%2felectronics12010171&partnerID=40&md5=5092c418bc0352fb7338c92a87f8f0dc
relation: 10.3390/electronics12010171
identifier: 10.3390/electronics12010171