提出事件驱动通信的机器人任务分配方法，显著减少消息传输量。
Event Driven CBBA with Reduced Communication
- 基于事件触发机制，仅在必要时通信，降低频次。
- 仿真显示消息量最多减少52%，且保持原算法性能。
- 适合通信受限的多无人机协同任务场景。
在多无人机监控与搜救等场景中，需部署多台机器人并行完成任务。由于车辆通信范围有限，去中心化任务分配算法至关重要。共识束算法（CBBA）虽具理论保障，但依赖持续通信，易引发拥塞和丢包，影响性能。本文提出事件驱动通信机制（ED-CBBA），在保持CBBA收敛性与性能边界前提下，解决通信瓶颈。理论上证明其解质量与CBBA一致，并通过蒙特卡洛模拟在不同目标数、代理数和任务包规模下验证。结果表明，该算法可使消息传输量最多减少52%。
原文摘要 · Abstract (English)
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%.
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