Ondřej Procházka presents MPC-based trajectory generation for agile landing of unmanned aerial vehicle on a moving boat

During the seminar, we will present our novel model predictive control-based
trajectory generation method enabling precise and fast UAV landings on tilting
USVs in rough seas.

Reference:
Ondřej Procházka, Filip Novák, Tomáš Báča, Parakh M Gupta, Robert
Pěnička and Martin Saska. Model predictive control-based trajectory
generation
for agile landing of unmanned aerial vehicle on a moving boat. Ocean
Engineering
313:119164, 2024.

Paper 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.

Link: https://doi.org/10.1016/j.oceaneng.2024.119164