McLoughlin BJ, Pointon HAG, McLoughlin JP, Shaw A, Bezombes FA. Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments.
Sensors (Basel) 2018;
18:s18072274. [PMID:
30011874 PMCID:
PMC6068590 DOI:
10.3390/s18072274]
[Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 07/07/2018] [Accepted: 07/11/2018] [Indexed: 11/16/2022]
Abstract
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.
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