研究机器人通过相遇传递信息的传播规律,揭示影响跟踪精度的三大瓶颈。
A Kinetic Theory of Encounter-Based Information Propagation in Multi-Robot Systems

- 基于机器人相遇机制建模信息传播,提出动力学理论框架。
- 发现信息可达性、时效性和几何限制三类极限,决定跟踪误差上限。
- 适用于无持续连接的多机器人系统设计,如搜救、巡检任务。
多机器人系统无法依赖持续网络连接。本文以目标跟踪为例,研究信息感知、传输与使用前的时效性问题。当机器人仅通过物理相遇交换信息时,跟踪演化为一种动能信息传输问题:机器人运动引发相遇,相遇携带目标状态估计,信息年龄决定过时程度,过时信息导致跟踪误差。本文建立相遇式信息传播的动力学理论,识别出三个极限:访问极限——信息需扩散至感知者之外才能支持团队协调;时效极限——即使传播,信息随目标移动而贬值;几何极限——当目标运动快于信息传输时,跟踪误差趋于饱和,单纯提升通信效果收益递减。通过大规模仿真,验证了访问-时效-几何的分解结构:通信覆盖控制访问过渡;一旦信息可及,误差主要由目标位移决定;局部呈线性,全局因感知刷新和空间约束呈现非线性。在不同团队规模、区域、通信范围与目标速度下,推导的访问与时效坐标能稳定描述跟踪性能。该成果为设计相遇式多机器人系统提供了理论预测框架。
原文摘要 · Abstract (English)
Multi-robot systems cannot assume persistent network connectivity. We study this problem through target tracking, where performance depends on how quickly target information is sensed, transported through the team, and used before it becomes stale. When robots exchange information only through physical encounters, tracking becomes a kinetic information-transport problem: robot motion induces encounters, encounters carry target-state estimates, information age determines staleness, and stale information produces tracking error. This paper develops a kinetic theory of encounter-based information propagation and identifies three limits. The first is an access limit -- information cannot support team-level coordination unless it spreads beyond the robots that sensed it. The second is a staleness limit -- even propagated information loses value as the target moves. The third is a geometry limit -- when target motion outpaces information transport, tracking error approaches a saturation regime where communication improvements alone have diminishing returns. We evaluate the theory through large-scale simulations varying team size, operating area, communication range, and target speed. Results support the proposed access-staleness-geometry decomposition: communication coverage governs the access transition; once information is accessible, tracking error is shaped by target displacement; and this response is locally linear in restricted regimes but nonlinear over broader ranges because of sensing refreshes and bounded geometry. Across controlled sweeps and joint variation, the derived access and staleness coordinates reliably describe tracking performance. Together, these results establish a kinetic-theoretic framework for predicting and designing encounter-based multi-robot systems.
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