Efficient Swarm Consensus: Comparative Evaluation of RLR vs Raft, RaBFT and VSSB-Raft

Abstract

Consensus mechanisms are essential in swarm robotics to maintain uniformity of decisions and states across distributed agents. Earlier methods often relied on approaches such as majority voting, averaging techniques, or leader election. In recent years, blockchain-based algorithms including Proof of Work (PoW), Proof of Stake (PoS), Practical Byzantine Fault Tolerance (PBFT), and Raft have been adopted for this purpose. While these methods provide certain advantages, their application to swarm robotics is restricted by issues such as limited computational power, energy constraints, scalability challenges caused by message complexity and latency, and weak protection against Byzantine agents. This study introduces a consensus approach specifically designed to address these gaps and to improve collaborative decision-making in swarm environments. The work outlines the motivation for the proposed solution, describes the simulation-based experimental design, and presents a detailed analysis of the observed results.