SFG-ROS: A Resource-Aware Framework for Dense Multi-Agent Perception
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911709299474432 |
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| author | Blessing, Constantin Geiger, Elias Häringer, Jakob Grewe, Dennis Enzweiler, Markus |
| author_facet | Blessing, Constantin Geiger, Elias Häringer, Jakob Grewe, Dennis Enzweiler, Markus |
| contents | Deploying heterogeneous multi-agent robot fleets for collaborative perception requires robust data exchange and scalable software architectures. However, standard ROS 2 implementations often suffer from network saturation, namespace collisions, and severe computational overhead when distributing dense sensor streams across devices. To address these bottlenecks, we present SFG-ROS, a resource-aware multi-agent software framework designed for dynamic fleet deployments. SFG-ROS addresses these challenges through three primary contributions. First, schema-driven traffic routing isolates high-frequency intra-agent traffic from the global network using a programmatic fully qualified name schema and targeted Fast DDS routing. Second, an on-demand centralized decoding pipeline automatically offloads high-bandwidth sensor data decompression, eliminating redundant processing across local consumer nodes. Finally, a hardware-agnostic container pipeline dynamically adapts to heterogeneous accelerators, seamlessly bridging development environments with zero-touch, field-ready execution. We evaluate the framework using a fleet of wheeled and legged robots equipped with LiDAR and stereo depth cameras. Experimental results show SFG-ROS bounds network traffic to $\mathcal{O}(1)$ and, by replacing redundant decompression with lightweight IPC, reduces the per-subscriber CPU scaling penalty by 72.3\% versus standard ROS 2, all while maintaining low latency. Finally, we publish SFG-ROS under a permissive license, available via \href{https://iis-esslingen.github.io/sfg-ros}{iis-esslingen.github.io/sfg-ros}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_23832 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SFG-ROS: A Resource-Aware Framework for Dense Multi-Agent Perception Blessing, Constantin Geiger, Elias Häringer, Jakob Grewe, Dennis Enzweiler, Markus Robotics Deploying heterogeneous multi-agent robot fleets for collaborative perception requires robust data exchange and scalable software architectures. However, standard ROS 2 implementations often suffer from network saturation, namespace collisions, and severe computational overhead when distributing dense sensor streams across devices. To address these bottlenecks, we present SFG-ROS, a resource-aware multi-agent software framework designed for dynamic fleet deployments. SFG-ROS addresses these challenges through three primary contributions. First, schema-driven traffic routing isolates high-frequency intra-agent traffic from the global network using a programmatic fully qualified name schema and targeted Fast DDS routing. Second, an on-demand centralized decoding pipeline automatically offloads high-bandwidth sensor data decompression, eliminating redundant processing across local consumer nodes. Finally, a hardware-agnostic container pipeline dynamically adapts to heterogeneous accelerators, seamlessly bridging development environments with zero-touch, field-ready execution. We evaluate the framework using a fleet of wheeled and legged robots equipped with LiDAR and stereo depth cameras. Experimental results show SFG-ROS bounds network traffic to $\mathcal{O}(1)$ and, by replacing redundant decompression with lightweight IPC, reduces the per-subscriber CPU scaling penalty by 72.3\% versus standard ROS 2, all while maintaining low latency. Finally, we publish SFG-ROS under a permissive license, available via \href{https://iis-esslingen.github.io/sfg-ros}{iis-esslingen.github.io/sfg-ros}. |
| title | SFG-ROS: A Resource-Aware Framework for Dense Multi-Agent Perception |
| topic | Robotics |
| url | https://arxiv.org/abs/2605.23832 |