Hybrid ACO for Blockchain-Managed Robotic Swarms*

Abstract

We present a dynamic multi-robot mapping framework that combines Blockchain technology for swarm management with a Hybrid Ant Colony Optimization (HACO) algorithm for path planning. Blockchain-based swarm contracts enable decentralized, transparent, and secure task allocation, acceptance, tracking, and reward distribution among multiple robots. HACO facilitates efficient path planning in complex environments through cooperative and competitive strategies. We deploy multiple LiDAR-equipped Unitree Go2 dog robots to collaboratively and competitively map divided sub-areas, with task reassignment based on real-time feedback and the selected strategy. In cooperative mode, robots share data to boost efficiency and accuracy; in competitive mode, they work independently to reduce redundancy and optimize resources. Swarm contracts also verify full sub-area coverage via the merged map. Results show that integrating blockchain-based management with HACO significantly enhances mapping performance, delivering a robust and scalable solution for realworld multi-robot systems.