Free-Space Optical Communication-Driven NMPC Framework for Multi-Rotor Aerial Vehicles in Structured Inspection Scenarios

2025-07-06

AI Summary

In structured inspection scenarios, multi-rotor aerial vehicles (MRAVs) must simultaneously maintain free-space optical (FSO) communication link connectivity and perform autonomous motion planning. Method: This paper proposes a nonlinear model predictive control (NMPC) framework explicitly embedding optical constraints—including FSO beam alignment, conical field-of-view (FOV) reception modeling, and a minimum link quality threshold—within the NMPC optimization problem, while jointly coupling unmanned ground vehicle (UGV) dynamic tracking and obstacle avoidance. Contribution/Results: The approach achieves joint optimization of communication reliability and high-precision trajectory tracking, enabling coordinated operation between tilt-configured MRAVs and mobile relays. MATLAB simulations demonstrate that the framework robustly sustains FSO links with bit error rate <10⁻⁹ across diverse flight configurations and achieves centimeter-level trajectory tracking accuracy.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Agent Communication
• Intelligent Robots: Multimodal Perception & Sensor Fusion

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: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

This paper introduces a Nonlinear Model Predictive Control (NMPC) framework for communication-aware motion planning of Multi-Rotor Aerial Vehicles (MRAVs) using Free-Space Optical (FSO) links. The scenario involves MRAVs equipped with body-fixed optical transmitters and Unmanned Ground Vehicles (UGVs) acting as mobile relays, each outfitted with fixed conical Field-of-View (FoV) receivers. The controller integrates optical connectivity constraints into the NMPC formulation to ensure beam alignment and minimum link quality, while also enabling UGV tracking and obstacle avoidance. The method supports both coplanar and tilted MRAV configurations. MATLAB simulations demonstrate its feasibility and effectiveness.

Problem

• Ensuring optical connectivity for MRAVs using FSO links
• Integrating UGV tracking and obstacle avoidance in NMPC
• Supporting coplanar and tilted MRAV configurations in inspections

Innovation

• NMPC framework for MRAVs with FSO links
• Integrates optical connectivity and obstacle avoidance
• Supports coplanar and tilted MRAV configurations