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Gyro sensor drift compensation by Kalman filter to control a mobile inverted pendulum robot system
In this paper, a sensor fusion technique of low cost sensors such as a gyro sensor and a tilt sensor to measure the balancing angle of the inverted pendulum robot system accurately is implemented. The complimentary filter consisting of the lowpass filter for the gyro sensor and the highpass filter f...
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creator | Hyung-Jik Lee Seul Jung |
description | In this paper, a sensor fusion technique of low cost sensors such as a gyro sensor and a tilt sensor to measure the balancing angle of the inverted pendulum robot system accurately is implemented. The complimentary filter consisting of the lowpass filter for the gyro sensor and the highpass filter for the tilt sensor are used based on the frequency response characteristics of those sensors. The Kalman filter is used to estimate the angle based on filtered sensor data. Experimental studies of balancing and position control of the mobile inverted pendulum robot system are conducted to validate the proposed estimation method. |
doi_str_mv | 10.1109/ICIT.2009.4939502 |
format | conference_proceeding |
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The complimentary filter consisting of the lowpass filter for the gyro sensor and the highpass filter for the tilt sensor are used based on the frequency response characteristics of those sensors. The Kalman filter is used to estimate the angle based on filtered sensor data. Experimental studies of balancing and position control of the mobile inverted pendulum robot system are conducted to validate the proposed estimation method.</description><identifier>ISBN: 1424435064</identifier><identifier>ISBN: 9781424435067</identifier><identifier>EISBN: 1424435072</identifier><identifier>EISBN: 9781424435074</identifier><identifier>DOI: 10.1109/ICIT.2009.4939502</identifier><identifier>LCCN: 2008911103</identifier><language>eng</language><publisher>IEEE</publisher><subject>complementary filter ; Control systems ; Costs ; Filters ; Frequency response ; Goniometers ; gyro drift ; Inverted pendulum ; Kalman filter ; Mobile robots ; Robot sensing systems ; Sensor fusion ; Sensor phenomena and characterization ; Sensor systems</subject><ispartof>2009 IEEE International Conference on Industrial Technology, 2009, p.1-6</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4939502$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,778,782,787,788,2054,27912,54907</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4939502$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hyung-Jik Lee</creatorcontrib><creatorcontrib>Seul Jung</creatorcontrib><title>Gyro sensor drift compensation by Kalman filter to control a mobile inverted pendulum robot system</title><title>2009 IEEE International Conference on Industrial Technology</title><addtitle>ICIT</addtitle><description>In this paper, a sensor fusion technique of low cost sensors such as a gyro sensor and a tilt sensor to measure the balancing angle of the inverted pendulum robot system accurately is implemented. The complimentary filter consisting of the lowpass filter for the gyro sensor and the highpass filter for the tilt sensor are used based on the frequency response characteristics of those sensors. The Kalman filter is used to estimate the angle based on filtered sensor data. Experimental studies of balancing and position control of the mobile inverted pendulum robot system are conducted to validate the proposed estimation method.</description><subject>complementary filter</subject><subject>Control systems</subject><subject>Costs</subject><subject>Filters</subject><subject>Frequency response</subject><subject>Goniometers</subject><subject>gyro drift</subject><subject>Inverted pendulum</subject><subject>Kalman filter</subject><subject>Mobile robots</subject><subject>Robot sensing systems</subject><subject>Sensor fusion</subject><subject>Sensor phenomena and characterization</subject><subject>Sensor systems</subject><isbn>1424435064</isbn><isbn>9781424435067</isbn><isbn>1424435072</isbn><isbn>9781424435074</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpFUM1qwzAY8xiFrV0fYOzyvUAy_ybxcYStDSvsknuxYwc8krjY7iBvP8MK00UIJCGE0DPBJSFYvnZt15cUY1lyyaTA9A5tCaecM4Frev8vKr5B22xsJMlB9oD2MX7jDC4YodUj0oc1eIh2iT6ACW5MMPj5krVKzi-gV_hU06wWGN2UbIDks2FJwU-gYPbaTRbc8mNDsgZyzlyn6wzBa58grjHZ-QltRjVFu7_xDvUf7317LE5fh659OxVO4lQwzE3VCGulHHitmcQ6L66FaYTQrJJYalUxTYRhuq7oWFNRE8WNNBRTMzRsh17-ap219nwJblZhPd_-Yb_GJ1fG</recordid><startdate>200902</startdate><enddate>200902</enddate><creator>Hyung-Jik Lee</creator><creator>Seul Jung</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200902</creationdate><title>Gyro sensor drift compensation by Kalman filter to control a mobile inverted pendulum robot system</title><author>Hyung-Jik Lee ; Seul Jung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-304d685ee99c47b390b11075d855b36909ba63b15d3b762f72571a4d9d202dc83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>complementary filter</topic><topic>Control systems</topic><topic>Costs</topic><topic>Filters</topic><topic>Frequency response</topic><topic>Goniometers</topic><topic>gyro drift</topic><topic>Inverted pendulum</topic><topic>Kalman filter</topic><topic>Mobile robots</topic><topic>Robot sensing systems</topic><topic>Sensor fusion</topic><topic>Sensor phenomena and characterization</topic><topic>Sensor systems</topic><toplevel>online_resources</toplevel><creatorcontrib>Hyung-Jik Lee</creatorcontrib><creatorcontrib>Seul Jung</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hyung-Jik Lee</au><au>Seul Jung</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Gyro sensor drift compensation by Kalman filter to control a mobile inverted pendulum robot system</atitle><btitle>2009 IEEE International Conference on Industrial Technology</btitle><stitle>ICIT</stitle><date>2009-02</date><risdate>2009</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><isbn>1424435064</isbn><isbn>9781424435067</isbn><eisbn>1424435072</eisbn><eisbn>9781424435074</eisbn><abstract>In this paper, a sensor fusion technique of low cost sensors such as a gyro sensor and a tilt sensor to measure the balancing angle of the inverted pendulum robot system accurately is implemented. The complimentary filter consisting of the lowpass filter for the gyro sensor and the highpass filter for the tilt sensor are used based on the frequency response characteristics of those sensors. The Kalman filter is used to estimate the angle based on filtered sensor data. Experimental studies of balancing and position control of the mobile inverted pendulum robot system are conducted to validate the proposed estimation method.</abstract><pub>IEEE</pub><doi>10.1109/ICIT.2009.4939502</doi><tpages>6</tpages></addata></record> |
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subjects | complementary filter Control systems Costs Filters Frequency response Goniometers gyro drift Inverted pendulum Kalman filter Mobile robots Robot sensing systems Sensor fusion Sensor phenomena and characterization Sensor systems |
title | Gyro sensor drift compensation by Kalman filter to control a mobile inverted pendulum robot system |
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