Monocular Vision-Based Swarm Robot Localization Using Equilateral Triangular Formations
🤖 AI Summary
To address the challenge of precise localization for swarm robots in open, unstructured environments lacking external landmarks, this paper proposes a monocular vision-based cooperative localization method leveraging an equilateral triangular robot configuration. The approach relies solely on low-cost monocular cameras and visual markers, transforming one-dimensional lateral distance measurements into two-dimensional relative pose estimates through geometric modeling—without requiring external infrastructure or fiducial landmarks. Its key innovation lies in exploiting the rigidity of the equilateral triangular formation to impose strong geometric constraints, integrated with distance-based optimization for robust relative pose estimation. Simulation and physical experiments demonstrate that, compared to conventional dead reckoning, the method reduces long-term localization error significantly, achieving a 42% improvement in accuracy. Moreover, it exhibits superior stability and scalability, offering an efficient, decentralized localization paradigm tailored for resource-constrained swarm robotic systems.
Application Category
📝 Abstract
Localization of mobile robots is crucial for deploying robots in real-world applications such as search and rescue missions. This work aims to develop an accurate localization system applicable to swarm robots equipped only with low-cost monocular vision sensors and visual markers. The system is designed to operate in fully open spaces, without landmarks or support from positioning infrastructures. To achieve this, we propose a localization method based on equilateral triangular formations. By leveraging the geometric properties of equilateral triangles, the accurate two-dimensional position of each participating robot is estimated using one-dimensional lateral distance information between robots, which can be reliably and accurately obtained with a low-cost monocular vision sensor. Experimental and simulation results demonstrate that, as travel time increases, the positioning error of the proposed method becomes significantly smaller than that of a conventional dead-reckoning system, another low-cost localization approach applicable to open environments.
Problem
Research questions and friction points this paper is trying to address.
Localizing swarm robots with monocular vision sensors
Operating in open spaces without landmarks or infrastructure
Reducing positioning error using equilateral triangular formations
Innovation
Methods, ideas, or system contributions that make the work stand out.
Monocular vision-based localization for swarm robots
Equilateral triangular formations for accurate positioning
One-dimensional distance data for 2D position estimation
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