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From Coupled Dynamics to Autonomous Missions: A Review of Quadrotor with Cable-Suspended Payload

Oct 2026 · Drones · 0 citations

Abstract

Quadrotors with cable-suspended payloads have received more attention among researchers in the aerial transportation, delivery, infrastructure inspection, emergency response, precision agriculture, and operations in hazardous environment applications. Cable suspension provides mechanical separation between the vehicle and payload, improving operational flexibility and safety compared with rigidly attached loads. However, it introduces nonlinear coupling, underactuation, payload swing, cable-tension variations, aerodynamic disturbances, and complex control challenges. This paper presents a comprehensive review of quadrotor systems with cable-suspended payloads, focusing on coupled dynamics, aerodynamic modeling, stability, control, fault tolerance, and mission planning. Suspended-payload configurations, cable mechanisms, and single- and multi-UAV transportation systems are discussed. Dynamic modeling approaches, including Newton–Euler, Euler–Lagrange, Kane’s method, geometric modeling, flexible-cable representations, and simulation-based frameworks, are compared. Rotor aerodynamic modeling is also reviewed, with attention to the differences among conventional empirical thrust models, full Blade Element Momentum Theory (BEMT), and reduced-order BEMT-informed formulations, particularly in relation to wind- and inflow-dependent rotor behavior. Control methods for trajectory tracking, payload-swing suppression, cable-tension regulation, and disturbance rejection are reviewed alongside passive, active, observer-based, adaptive, and learning-assisted fault-tolerant strategies. Mission-planning methods are examined with respect to wind-aware routing, obstacle avoidance, energy use, payload constraints, online replanning, and safe delivery. Finally, major research gaps are identified, including simplified cable and payload assumptions, idealized rotor models, limited fault isolation, weak planning–control integration, and insufficient outdoor experimental validation.

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