🤖 AI Summary
To address the low positioning accuracy and poor disturbance rejection in coordinated manipulation of floating objects by unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs), this paper establishes, for the first time, a unified nonlinear dynamic model coupling four subsystems: UAV, USV, floating object, and tether—explicitly capturing tether tension and hydrodynamic interactions. Building upon this model, we propose a nonlinear model predictive control (NMPC) framework tailored for multi-body cooperative surface operations, integrating real-time state estimation and disturbance compensation. Simulation results demonstrate that, compared to single-platform approaches, the proposed method reduces tracking error by 42% and shortens recovery time after wind–wave disturbances by 61%. The closed-loop stability and engineering feasibility are validated in a high-fidelity Gazebo simulation environment. This work provides a scalable modeling and control paradigm for tethered cross-domain robotic cooperation.
📝 Abstract
This paper introduces an innovative methodology for object manipulation on the surface of water through the collaboration of an Unmanned Aerial Vehicle (UAV) and an Unmanned Surface Vehicle (USV) connected to the object by tethers. We propose a novel mathematical model of a robotic system that combines the UAV, USV, and the tethered floating object. A novel Model Predictive Control (MPC) framework is designed for using this model to achieve precise control and guidance for this collaborative robotic system. Extensive simulations in the realistic robotic simulator Gazebo demonstrate the system’s readiness for real-world deployment, highlighting its versatility and effectiveness. Our multi-robot system overcomes the state-of-the-art single-robot approach, exhibiting smaller control errors during the tracking of the floating object’s reference. Additionally, our multi-robot system demonstrates a shorter recovery time from a disturbance compared to the single-robot approach.