A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand
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Abstract (arXiv)
Despite the prevalence of wireless connectivity in urban areas around the globe, there remain numerous and diverse situations where connectivity is insufficient or unavailable. To address this, we introduce mobile wireless infrastructure on demand, a system of UAVs that can be rapidly deployed to establish an ad-hoc wireless network. This network has the capability of reconfiguring itself dynamically to satisfy and maintain the required quality of communication. The system optimizes the positions of the UAVs and the routing of data flows throughout the network to achieve this quality of service (QoS). By these means, task agents using the network simply request a desired QoS, and the system adapts accordingly while allowing them to move freely. We have validated this system both in simulation and in real-world experiments. The results demonstrate that our system effectively offers mobile wireless infrastructure on demand, extending the operational range of task agents and supporting complex mobility patterns, all while ensuring connectivity and being resilient to agent failures.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Jun 2023.
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Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025MoCom: Motion-based Inter-MAV Visual Communication Using Event Vision and Spiking Neural Networkscited by 3
- 2025Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial-Ground Robotic Systemcited by 2
- 2025MAVR-Net: Robust Multi-View Learning for MAV Action Recognition with Cross-View Attentioncited by 1
- 2025MobiAct: Efficient MAV Action Recognition Using MobileNetV4 with Contrastive Learning and Knowledge Distillationcited by 0
- 2026Adjacency-Based Spectral Proxy Control of Mobile Communication Agentscited by 0
- 2026Adjacency-Based Spectral Proxy Control of Mobile Communication Agents12 Aug 2026
- 2025MobiAct: Efficient MAV Action Recognition Using MobileNetV4 with Contrastive Learning and Knowledge Distillation22 Oct 2025
- 2025MAVR-Net: Robust Multi-View Learning for MAV Action Recognition with Cross-View Attention17 Oct 2025
- 2025MoCom: Motion-based Inter-MAV Visual Communication Using Event Vision and Spiking Neural Networks16 Oct 2025
- 2025Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial-Ground Robotic System5 Jun 2025