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 |
| Published: |
MDPI AG
2018-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/7/2274 |
| Summary: | 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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| ISSN: | 1424-8220 |