🤖 AI Summary
Distributed heterogeneous modular space robotic systems face significant challenges in architectural design and dynamic deployment across diverse computing platforms, network conditions, and planetary environments. Method: This paper proposes a distributed heterogeneous modular design paradigm integrating software components, communication infrastructure, and orchestration layers. Leveraging component-based principles, it establishes a reusable architecture supporting dynamic reconfiguration, decentralized control, and multi-module coordination. The approach integrates ROS 2 with the Zenoh data-centric middleware for low-latency, high-reliability communication, incorporates an open-source motion stack, and introduces a lightweight deployment orchestrator. Contribution/Results: Extensive field validation demonstrates robust support for self-assembling robots, multi-robot collaboration, and teleoperation. The system substantially reduces integration and maintenance overhead while enabling universal deployment across heterogeneous hardware platforms, development teams, and mission-specific operational environments.
📝 Abstract
This paper presents the software architecture and deployment strategy behind the MoonBot platform: a modular space robotic system composed of heterogeneous components distributed across multiple computers, networks and ultimately celestial bodies. We introduce a principled approach to distributed, heterogeneous modularity, extending modular robotics beyond physical reconfiguration to software, communication and orchestration. We detail the architecture of our system that integrates component-based design, a data-oriented communication model using ROS2 and Zenoh, and a deployment orchestrator capable of managing complex multi-module assemblies. These abstractions enable dynamic reconfiguration, decentralized control, and seamless collaboration between numerous operators and modules. At the heart of this system lies our open-source Motion Stack software, validated by months of field deployment with self-assembling robots, inter-robot cooperation, and remote operation. Our architecture tackles the significant hurdles of modular robotics by significantly reducing integration and maintenance overhead, while remaining scalable and robust. Although tested with space in mind, we propose generalizable patterns for designing robotic systems that must scale across time, hardware, teams and operational environments.