[2411.07056] Distributed Spatial Awareness for Robot Swarms
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:2411.07056 (cs)
[Submitted on 11 Nov 2024]

Title:Distributed Spatial Awareness for Robot Swarms

Authors:Simon Jones, Sabine Hauert
View PDF HTML (experimental)
Abstract:Building a distributed spatial awareness within a swarm of locally sensing and communicating robots enables new swarm algorithms. We use local observations by robots of each other and Gaussian Belief Propagation message passing combined with continuous swarm movement to build a global and distributed swarm-centric frame of reference. With low bandwidth and computation requirements, this shared reference frame allows new swarm algorithms. We characterise the system in simulation and demonstrate two example algorithms.
Comments: 17 pages, 7 figures. Presented at DARS 2024, accepted for publication in the Proceedings of DARS 2024, Springer SPAR series
Subjects: Robotics (cs.RO)
Cite as: arXiv:2411.07056 [cs.RO]
  (or arXiv:2411.07056v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2411.07056

Submission history

From: Simon Jones [view email]
[v1] Mon, 11 Nov 2024 15:17:53 UTC (973 KB)
Full-text links:

Access Paper:

license icon view license
Current browse context:
cs.RO
< prev   |   next >
new | recent | 2024-11
Change to browse by:
cs

References & Citations

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?)