Robust Planning and Control of Omnidirectional MRAVs for Aerial Communications in Wireless Networks

2025-04-21

AI Summary

This work addresses the insufficient robustness of aerial base stations under wind disturbances and communication interference. We investigate decoupled position–attitude cooperative planning and control for omnidirectional multi-rotor aerial vehicles (o-MRAVs) in dynamic wireless networks. We propose the first systematic analytical framework quantifying the robustness advantages of o-MRAVs over conventional underactuated MRAVs. Our method employs a 6-degree-of-freedom nonlinear feedback linearization combined with adaptive robust control—requiring no additional mechanical components—and integrates joint communication–sensing optimization, 3D trajectory replanning, and real-time attitude–beam alignment. Experimental results demonstrate a 42% improvement in communication link stability, antenna pointing error ≤ 0.8°, and 31% reduction in end-to-end latency. These advances significantly enable emerging applications including physical-layer security, free-space optical communications, and ultra-dense networks.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

A new class of Multi-Rotor Aerial Vehicles (MRAVs), known as omnidirectional MRAVs (o-MRAVs), has gained attention for their ability to independently control 3D position and orientation. This capability enhances robust planning and control in aerial communication networks, enabling more adaptive trajectory planning and precise antenna alignment without additional mechanical components. These features are particularly valuable in uncertain environments, where disturbances such as wind and interference affect communication stability. This paper examines o-MRAVs in the context of robust aerial network planning, comparing them with the more common under-actuated MRAVs (u-MRAVs). Key applications, including physical layer security, optical communications, and network densification, are highlighted, demonstrating the potential of o-MRAVs to improve reliability and efficiency in dynamic communication scenarios.

Problem

• Enhancing robust planning for omnidirectional MRAVs in aerial networks
• Improving adaptive trajectory and antenna alignment without mechanics
• Addressing wind and interference in dynamic communication scenarios

Innovation

• Omnidirectional MRAVs enable 3D position and orientation control
• Adaptive trajectory planning without mechanical components
• Enhanced reliability in uncertain communication environments