Model predictive control-based trajectory generation for agile landing of unmanned aerial vehicle on a moving boat

TL;DR

This paper introduces an MPC-based trajectory generation method enabling agile, precise UAV landings on moving USVs in rough sea conditions, with real-time onboard computation and improved accuracy over existing methods.

Contribution

The paper presents a novel MPC scheme that dynamically adapts to USV motion and deck inclination, enhancing landing precision and speed in challenging maritime environments.

Findings

Outperforms state-of-the-art methods in landing accuracy and speed

Achieves twice the precision in landing compared to existing approaches

Successfully demonstrates real-time onboard implementation in real-world tests

Abstract

This paper proposes a novel trajectory generation method based on Model Predictive Control (MPC) for agile landing of an Unmanned Aerial Vehicle (UAV) onto an Unmanned Surface Vehicle (USV)'s deck in harsh conditions. The trajectory generation exploits the state predictions of the USV to create periodically updated trajectories for a multirotor UAV to precisely land on the deck of a moving USV even in cases where the deck's inclination is continuously changing. We use an MPC-based scheme to create trajectories that consider both the UAV dynamics and the predicted states of the USV up to the first derivative of position and orientation. Compared to existing approaches, our method dynamically modifies the penalization matrices to precisely follow the corresponding states with respect to the flight phase. Especially during the landing maneuver, the UAV synchronizes attitude with the USV's, allowing for fast landing on a tilted deck. Simulations show the method's reliability in various sea conditions up to Rough sea (wave height 4 m), outperforming state-of-the-art methods in landing speed and accuracy, with twice the precision on average. Finally, real-world experiments validate the simulation results, demonstrating robust landings on a moving USV, while all computations are performed in real-time onboard the UAV.