aiqbench analysis
This research addresses the critical challenge of localization in swarm robotics by introducing a contact-driven method that eliminates reliance on external tracking infrastructure or expensive sensors. By utilizing binary contact information within a virtual-force framework, modular robots can iteratively refine their poses to achieve accurate self-assembly in unstructured environments without high-cost hardware. The approach demonstrates scalability for constructing diverse free-form structures like towers and cantilevers using only minimal onboard sensing capabilities.
Contact-Driven Localization in a Freeform Robotic Self-Assembled Structure
arXiv:2608.02895v1 Announce Type: new Abstract: Accurate localization remains a key challenge in swarm robotics, particularly for self-reconfigurable systems that must identify relative positions to form diverse structures. Most existing approaches rely on external tracking infrastructure or high-cost sensors, which limit scalability and deployment in unstructured environments. In this paper, we propose a novel contact-driven localization method for modular robots that leverages only local communication through binary contact information (whether two robots are physically connected or not). To exploit these contact cues, we introduce a virtual-force framework in which robots iteratively refine their poses attracting toward dock-connected neighbors and repelling from non-connected ones. The method requires no external infrastructure and relies only on minimal onboard sensing. Simulations show effective localization during the assembly of towers and cantilevers, enabling accurate, scalable, free-form self-assembly.
Abstract:Accurate localization remains a key challenge in swarm robotics, particularly for self-reconfigurable systems that must identify relative positions to form diverse structures. Most existing approaches rely on external tracking infrastructure or high-cost sensors, which limit scalability and deployment in unstructured environments. In this paper, we propose a novel contact-driven localization method for modular robots that leverages only local communication through binary contact information (whether two robots are physically connected or not). To exploit these contact cues, we introduce a virtual-force framework in which robots iteratively refine their poses attracting toward dock-connected neighbors and repelling from non-connected ones. The method requires no external infrastructure and relies only on minimal onboard sensing. Simulations show effective localization during the assembly of towers and cantilevers, enabling accurate, scalable, free-form self-assembly.
Robotics (cs.RO)
arXiv:2608.02895 [cs.RO]
(or arXiv:2608.02895v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.02895 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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.
Full text under the publisher's open licence · 219 words
Related coverage

NVIDIA GTC Taipei at COMPUTEX: Live Updates on What’s Next in AI
NVIDIA · May 21, 2026

BRICS Draws a New Global Line: Full Text of New Delhi Declaration
slguardian.org · Sep 12, 2026

Digital States 2026: AI Moves From Experiment to Infrastructure
govtech.com · Sep 24, 2026

Introducing Mistral OCR 4
Mistral AI · Jun 23, 2026