arXiv cs.MA· Madison Book, Justin Bradley·· 2 天前AI 评分18
基于可达性控制障碍函数的抢占式通信鲁棒多智能体追逃
Robust Multi-Agent Pursuit with Preemptive Communication via Reachability-Based Control Barrier Functions
AI 导读
该研究提出一种统一控制/通信策略，让每个智能体基于最后收到的邻居状态计算可达集，并用控制障碍函数求解安全控制输入，在通信间歇下保证智能体间避碰，前提是通信陈旧度有界。智能体依据不确定性与运动学风险指标决定何时抢占式发送自身状态。仿真显示，抢占式通信相比周期性和事件触发基线减少 77.5% 消息量，且零碰撞。
正文 · 原文
Abstract:Safe multi-agent coordination typically assumes what real-world, deployed, resource-constrained robots cannot provide: continuous, perfect state sharing. Robust control strategies must be complemented with robust communication strategies to deliver resilient deployments. In this work, we propose a unified control/communication strategy that provides safe control to guarantee inter-agent safety under intermittent communication and demonstrate its effectiveness in a pursuit-evasion scenario. Each agent computes the reachable set of neighboring agents based on the last state information received, then solves for a safe control input based on control barrier functions to ensure agents avoid collision. We prove that inter-agent collision avoidance is guaranteed provided communication staleness remains bounded. As the reachable set inflates between state transmissions, each agent reasons about when to preemptively transmit its state information to neighboring agents based on novel metrics characterizing uncertainty risk and kinematic risk. We implement and simulate a variety of pursuit-evasion scenarios and show that preemptive communication reduces messages by 77.5% compared to periodic and event-triggered baselines with zero collisions.
| Comments: | 6 pages, 4 figures. Accepted to the 2026 IEEE Conference on Decision and Control (CDC) |
| Subjects: | Systems and Control (eess.SY); Multiagent Systems (cs.MA); Robotics (cs.RO) |
| Cite as: | arXiv:2610.22198 [eess.SY] |
| (or arXiv:2610.22198v1 [eess.SY] for this version) | |
| https://doi.org/10.48550/arXiv.2610.22198 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Justin Bradley [view email]
[v1]
Thu, 15 Oct 2026 16:50:41 UTC (1,069 KB)
来源：arXiv cs.MA · arxiv.org