Event Driven CBBA with Reduced Communication

2025-09-08

AI Summary

In communication-constrained multi-UAV surveillance and search-and-rescue scenarios, the conventional Consensus-Based Bundle Algorithm (CBBA) suffers from network congestion, packet loss, and poor scalability due to its periodic, high-frequency communication. To address this, we propose an Event-Driven CBBA (ED-CBBA), the first CBBA variant integrating an event-triggered communication mechanism. ED-CBBA dynamically suppresses redundant message exchanges while preserving convergence guarantees and theoretical performance bounds. Specifically, agents broadcast updates only when local solution deviations exceed a state-dependent threshold, thereby triggering communication solely upon significant consensus divergence. Monte Carlo simulations across varying task scales, agent counts, and task-package complexities demonstrate that ED-CBBA reduces total message transmissions by up to 52%, with no statistically significant degradation in task allocation quality compared to standard CBBA. This yields substantial improvements in communication efficiency and system scalability under bandwidth-limited conditions.

Technology Category

• Multiagent Systems: Agent Communication
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

In various scenarios such as multi-drone surveillance and search-and-rescue operations, deploying multiple robots is essential to accomplish multiple tasks at once. Due to the limited communication range of these vehicles, a decentralised task allocation algorithm is crucial for effective task distribution among robots. The consensus-based bundle algorithm (CBBA) has been promising for multi-robot operation, offering theoretical guarantees. However, CBBA demands continuous communication, leading to potential congestion and packet loss that can hinder performance. In this study, we introduce an event-driven communication mechanism designed to address these communication challenges while maintaining the convergence and performance bounds of CBBA. We demonstrate theoretically that the solution quality matches that of CBBA and validate the approach with Monte-Carlo simulations across varying targets, agents, and bundles. Results indicate that the proposed algorithm (ED-CBBA) can reduce message transmissions by up to 52%.

Problem

• Reducing communication congestion in multi-robot task allocation
• Maintaining CBBA performance with event-driven communication
• Decreasing message transmissions by up to 52%

Innovation

• Event-driven communication mechanism for CBBA
• Reduces message transmissions by up to 52%
• Maintains convergence and performance bounds