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Open AccessArticle

Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments

Engineering and Technology Research Institute, Liverpool John Moores University, 3 Byrom St, Liverpool L3 3AF, UK
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Sensors 2018, 18(7), 2274; https://doi.org/10.3390/s18072274
Received: 15 June 2018 / Revised: 7 July 2018 / Accepted: 11 July 2018 / Published: 13 July 2018
(This article belongs to the Special Issue GNSS and Fusion with Other Sensors)
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. View Full-Text
Keywords: robotic total station; localisation; ultra wide-band; extended Kalman filter; RTS robotic total station; localisation; ultra wide-band; extended Kalman filter; RTS
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McLoughlin, B.J.; Pointon, H.A.G.; McLoughlin, J.P.; Shaw, A.; Bezombes, F.A. Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments. Sensors 2018, 18, 2274.

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