Contact-Driven Localization in a Freeform Robotic Self-Assembled Structure
Mohammadali Rashidioun, Michael Sosa, Petras Swissler
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.
Create a lesson
Related papers
rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference
Kaijun Zhou, Zhiyang Li, Le Chen et al.
ElastiQP: An Always-Feasible QP Solver for Constrained Robot Control
Daniel Morton, Jon Arrizabalaga, Zachary Manchester et al.
"What's going to happen after I'm gone?": Parent Perspectives on Technology in Supporting Independent Living for Adults with Intellectual Disabilities
Alexander Tyshka, Andrea Macklem-Zabel, Absalat Getachew et al.
Learning Holistic Whole-Body Loco-Manipulation with a Bipedal Mobile Manipulator
Zhongyu Chen, Yuxuan Nai, Qian Chen et al.
CaSCo: Cascade-Aware Soft-Collision Motion Planning
Shivaram Kumar, Gaoyuan Liu, Yoonchang Sung
Examining the Difference in Human Behavior Between Virtual and Real-World Human-Robot Teaming
Sean Dallas, Absalat Getachew, Motaz AbuHijleh et al.