Multi-robot collaboration in large-scale environments with limited-sized teams and without external infrastructure is challenging, since the software framework required to support complex tasks must be robust to unreliable and intermittent communication links. In this work, we present MOCHA (Multi-robot Opportunistic Communication for Heterogeneous Collaboration), a framework for resilient multi-robot collaboration that enables large-scale exploration in the absence of continuous communications. MOCHA is based on a gossip communication protocol that allows robots to interact opportunistically whenever communication links are available, propagating information on a peer-to-peer basis. We demonstrate the performance of MOCHA through real-world experiments with commercial-off-the-shelf (COTS) communication hardware. We further explore the system's scalability in simulation, evaluating the performance of our approach as the number of robots increases and communication ranges vary. Finally, we demonstrate how MOCHA can be tightly integrated with the planning stack of autonomous robots. We show a communication-aware planning algorithm for a high-altitude aerial robot executing a collaborative task while maximizing the amount of information shared with ground robots. The source code for MOCHA and the high-altitude UAV planning system is available open source: http://github.com/KumarRobotics/MOCHA, http://github.com/KumarRobotics/air_router.

翻译：在没有外部基础设施且团队规模受限的大规模环境中，多机器人协作面临挑战，因为支持复杂任务所需的软件框架必须能够应对不可靠且间歇性的通信链路。本文提出了MOCHA（面向异构协作的多机器人机会通信），一个用于弹性多机器人协作的框架，使机器人在缺乏持续通信的情况下也能实现大规模探索。MOCHA基于闲聊式通信协议，允许机器人在通信链路可用时进行机会性交互，以点对点方式传播信息。我们通过使用商用现成（COTS）通信硬件的实际实验展示了MOCHA的性能。进一步通过仿真探索了系统的可扩展性，评估了随着机器人数量增加和通信范围变化时本方法的性能。最后，我们展示了如何将MOCHA与自主机器人的规划堆栈紧密集成，为执行协作任务的高空飞行机器人设计了一种通信感知规划算法，该算法在最大化与地面机器人共享信息量的同时完成任务。MOCHA及高空无人机规划系统的源代码已开源：http://github.com/KumarRobotics/MOCHA，http://github.com/KumarRobotics/air_router。