Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments
Recent developments in localisation systems for autonomous robotic technology have been a driving factor in the deployment of robots in a wide variety of environments. Estimating sensor measurement noise is an essential factor when producing uncertainty models for state-of-the-art robotic positionin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/7/2274 |
| _version_ | 1828117330124603392 |
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| author | Benjamin J. McLoughlin Harry A. G. Pointon John P. McLoughlin Andy Shaw Frederic A. Bezombes |
| author_facet | Benjamin J. McLoughlin Harry A. G. Pointon John P. McLoughlin Andy Shaw Frederic A. Bezombes |
| author_sort | Benjamin J. McLoughlin |
| collection | DOAJ |
| description | Recent developments in localisation systems for autonomous robotic technology have been a driving factor in the deployment of robots in a wide variety of environments. Estimating sensor measurement noise is an essential factor when producing uncertainty models for state-of-the-art robotic positioning systems. In this paper, a surveying grade optical instrument in the form of a Trimble S7 Robotic Total Station is utilised to dynamically characterise the error of positioning sensors of a ground based unmanned robot. The error characteristics are used as inputs into the construction of a Localisation Extended Kalman Filter which fuses Pozyx Ultra-wideband range measurements with odometry to obtain an optimal position estimation, all whilst using the path generated from the remote tracking feature of the Robotic Total Station as a ground truth metric. Experiments show that the proposed method yields an improved positional estimation compared to the Pozyx systems’ native firmware algorithm as well as producing a smoother trajectory. |
| first_indexed | 2024-04-11T13:12:34Z |
| format | Article |
| id | doaj.art-5c2e060f3c074d4dbb4bece6c812bc5d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:12:34Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5c2e060f3c074d4dbb4bece6c812bc5d2022-12-22T04:22:29ZengMDPI AGSensors1424-82202018-07-01187227410.3390/s18072274s18072274Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade InstrumentsBenjamin J. McLoughlin0Harry A. G. Pointon1John P. McLoughlin2Andy Shaw3Frederic A. Bezombes4Engineering and Technology Research Institute, Liverpool John Moores University, 3 Byrom St, Liverpool L3 3AF, UKEngineering and Technology Research Institute, Liverpool John Moores University, 3 Byrom St, Liverpool L3 3AF, UKEngineering and Technology Research Institute, Liverpool John Moores University, 3 Byrom St, Liverpool L3 3AF, UKEngineering and Technology Research Institute, Liverpool John Moores University, 3 Byrom St, Liverpool L3 3AF, UKEngineering and Technology Research Institute, Liverpool John Moores University, 3 Byrom St, Liverpool L3 3AF, UKRecent developments in localisation systems for autonomous robotic technology have been a driving factor in the deployment of robots in a wide variety of environments. Estimating sensor measurement noise is an essential factor when producing uncertainty models for state-of-the-art robotic positioning systems. In this paper, a surveying grade optical instrument in the form of a Trimble S7 Robotic Total Station is utilised to dynamically characterise the error of positioning sensors of a ground based unmanned robot. The error characteristics are used as inputs into the construction of a Localisation Extended Kalman Filter which fuses Pozyx Ultra-wideband range measurements with odometry to obtain an optimal position estimation, all whilst using the path generated from the remote tracking feature of the Robotic Total Station as a ground truth metric. Experiments show that the proposed method yields an improved positional estimation compared to the Pozyx systems’ native firmware algorithm as well as producing a smoother trajectory.http://www.mdpi.com/1424-8220/18/7/2274robotic total stationlocalisationultra wide-bandextended Kalman filterRTS |
| spellingShingle | Benjamin J. McLoughlin Harry A. G. Pointon John P. McLoughlin Andy Shaw Frederic A. Bezombes Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments Sensors robotic total station localisation ultra wide-band extended Kalman filter RTS |
| title | Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments |
| title_full | Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments |
| title_fullStr | Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments |
| title_full_unstemmed | Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments |
| title_short | Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments |
| title_sort | uncertainty characterisation of mobile robot localisation techniques using optical surveying grade instruments |
| topic | robotic total station localisation ultra wide-band extended Kalman filter RTS |
| url | http://www.mdpi.com/1424-8220/18/7/2274 |
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