在通信受限下,实现多操作员多机器人在线协同与动态拓扑调整。
MoRoCo: An Online Topology-Adaptive Framework for Multi-Operator Multi-Robot Coordination under Restricted Communication
- 基于延迟约束的间歇通信骨架,支持实时信息传递。
- 通过拆分与重组机制,动态适应不同通信需求。
- 适合复杂环境下的搜救、勘探等需人机协同的任务。
在通信受限的场景中,如地下探测、侦察和搜救任务,越来越多自主机器人车队由多名操作员协同控制。此时通信仅能依赖短距离自组网络,难以兼顾探索协调与在线人机交互。现有研究多关注信息采集本身,却忽视操作员在执行中发出的时序关键请求,这些请求对通信结构要求各异——从间歇状态传输到持续视频流或远程操控。为此,本文提出 MoRoCo,一种面向受限通信的多操作员多机器人在线拓扑自适应框架。该框架基于延迟约束的间歇通信骨干网,确保任意机器人采集的信息在规定延迟内送达操作员;并引入“脱离-重新加入”机制,支持在线团队规模调整与拓扑重构。在此基础上,框架通过联合分配机器人角色、位置与通信拓扑,实例化一致于请求的通信子图,实现多种人机交互模式。其进一步支持仅依赖本地通信的子图在线分解与组合,使多个请求可在探索过程中同时被服务。框架还扩展至异构车队、多团队及机器人故障场景。大量人机在环仿真与硬件实验验证了其在受限通信下的高效可靠协作能力。
原文摘要 · Abstract (English)
Fleets of autonomous robots are increasingly deployed with multiple human operators in communication-restricted environments for exploration and intervention tasks such as subterranean inspection, reconnaissance, and search-and-rescue. In these settings, communication is often limited to short-range ad-hoc links, making it difficult to coordinate exploration while supporting online human-fleet interactions. Existing work on multi-robot exploration largely focuses on information gathering itself, but pays limited attention to the fact that operators and robots issue time-critical requests during execution. These requests may require different communication structures, ranging from intermittent status delivery to sustained video streaming and teleoperation. To address this challenge, this paper presents MoRoCo, an online topology-adaptive framework for multi-operator multi-robot coordination under restricted communication. MoRoCo is built on a latency-bounded intermittent communication backbone that guarantees a prescribed delay for information collected by any robot to reach an operator, together with a detach-and-rejoin mechanism that enables online team resizing and topology reconfiguration. On top of this backbone, the framework instantiates request-consistent communication subgraphs to realize different modes of operator-robot interaction by jointly assigning robot roles, positions, and communication topology. It further supports the online decomposition and composition of these subgraphs using only local communication, allowing multiple requests to be serviced during exploration. The framework extends to heterogeneous fleets, multiple teams, and robot failures. Extensive human-in-the-loop simulations and hardware experiments demonstrate effective and reliable coordination under restricted communication.
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