Distributed Model Predictive Control for Cooperative Multirotor Landing on Uncrewed Surface Vessel in Waves
CoRR(2024)
Abstract
Heterogeneous autonomous robot teams consisting of multirotor and uncrewed
surface vessels (USVs) have the potential to enable various maritime
applications, including advanced search-and-rescue operations. A critical
requirement of these applications is the ability to land a multirotor on a USV
for tasks such as recharging. This paper addresses the challenge of safely
landing a multirotor on a cooperative USV in harsh open waters. To tackle this
problem, we propose a novel sequential distributed model predictive control
(MPC) scheme for cooperative multirotor-USV landing. Our approach combines
standard tracking MPCs for the multirotor and USV with additional artificial
intermediate goal locations. These artificial goals enable the robots to
coordinate their cooperation without prior guidance. Each vehicle solves an
individual optimization problem for both the artificial goal and an input that
tracks it but only communicates the former to the other vehicle. The artificial
goals are penalized by a suitable coupling cost. Furthermore, our proposed
distributed MPC scheme utilizes a spatial-temporal wave model to coordinate in
real-time a safer landing location and time the multirotor's landing to limit
severe tilt of the USV.
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Key words
Model Predictive Control,Surface Vessels,Distributed Model Predictive Control,Distributed Control,Wave Model,Local Land,Model Predictive Control Strategy,Standard Tracking,Predictive Control Strategy,Safe Location,Distributed Control Strategy,Spatial-temporal Model,Time Step,Value Function,Kernel Function,Nonlinear Dynamics,Unmanned Aerial Vehicles,Kriging,Tilt Angle,Multi-agent Systems,Cost Of Cooperation,Current Goals,Calm Water,Query Point,Wave Trough,World Frame,Skew-symmetric,Prediction Horizon,Gravity Vector
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