Abstract
One of the most fundamental tasks for robots inspecting water distribution pipes is localization, which allows for autonomous navigation, for faults to be communicated, and for interventions to be instigated. Pose-graph optimization using spatially varying information is used to enable localization within a feature-sparse length of pipe. We present a novel method for improving estimation of a robot’s trajectory using the measured acoustic field, which is applicable to other measurements such as magnetic field sensing. Experimental results show that the use of acoustic information in pose-graph optimization reduces errors by 39% compared to the use of typical pose-graph optimization using landmark features only. High location accuracy is essential to efficiently and effectively target investment to maximise the use of our aging pipe infrastructure.
| Original language | English |
|---|---|
| Article number | 5584 |
| Pages (from-to) | 1-23 |
| Number of pages | 23 |
| Journal | Sensors (Switzerland) |
| Volume | 20 |
| Issue number | 19 |
| DOIs | |
| Publication status | Published - 29 Sept 2020 |
Bibliographical note
Publisher Copyright:© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Funding
This research was funded by an EPSRC Doctoral Training Partnership Scholarship and is supported by EPSRC grant EP/S016813/1 (Pipebots). The APC was funded by EPSRC.
Keywords
- Pipe inspection robot
- Pose-graph optimization
- Robot localization and mapping
- SLAM
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