Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Robotics

arXiv:2109.04868 (cs)
[Submitted on 10 Sep 2021]

Title:Heading Estimation Using Ultra-Wideband Received Signal Strength and Gaussian Processes

Authors:Daniil Lisus, Charles Champagne Cossette, Mohammed Shalaby, James Richard Forbes
View PDF
Abstract:It is essential that a robot has the ability to determine its position and orientation to execute tasks autonomously. Heading estimation is especially challenging in indoor environments where magnetic distortions make magnetometer-based heading estimation difficult. Ultra-wideband (UWB) transceivers are common in indoor localization problems. This letter experimentally demonstrates how to use UWB range and received signal strength (RSS) measurements to estimate robot heading. The RSS of a UWB antenna varies with its orientation. As such, a Gaussian process (GP) is used to learn a data-driven relationship from UWB range and RSS inputs to orientation outputs. Combined with a gyroscope in an invariant extended Kalman filter, this realizes a heading estimation method that uses only UWB and gyroscope measurements.
Comments: 6 pages, 9 figures, accepted to Robotics and Automation Letters, presented at IROS 2021
Subjects: Robotics (cs.RO); Machine Learning (cs.LG)
Cite as: arXiv:2109.04868 [cs.RO]
  (or arXiv:2109.04868v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2109.04868
Journal reference: in IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8387-8393, Oct. 2021
Related DOI: https://doi.org/10.1109/LRA.2021.3102300

Submission history

From: Daniil Lisus [view email]
[v1] Fri, 10 Sep 2021 13:28:23 UTC (4,711 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.RO
< prev   |   next >
new | recent | 2021-09
Change to browse by:
cs
cs.LG

References & Citations

DBLP - CS Bibliography

listing | bibtex
James Richard Forbes
export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)