A nonlinear model predictive controller, tested in high-fidelity simulation, lets the M4 morphing robot recover from a fully failed rotor by reconfiguring its legs and remaining thrusters.
Modeling and Controls of Fluid-Structure Interactions (FSI) in Dynamic Morphing Flight
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abstract
The primary aim of this study is to enhance the accuracy of our aerodynamic Fluid-Structure Interaction (FSI) model to support the controlled tracking of 3D flight trajectories by Aerobat, which is a dynamic morphing winged drone. Building upon our previously documented Unsteady Aerodynamic model rooted in horseshoe vortices, we introduce a new iteration of Aerobat, labeled as version beta, which is designed for attachment to a Kinova arm. Through a series of experiments, we gather force-moment data from the robotic arm attachment and utilize it to fine-tune our unsteady model for banking turn maneuvers. Subsequently, we employ the tuned FSI model alongside a collocation control strategy to accomplish 3D banking turns of Aerobat within simulation environments. The primary contribution lies in presenting a methodical approach to calibrate our FSI model to predict complex 3D maneuvers and successfully assessing the model's potential for closed-loop flight control of Aerobat using an optimization-based collocation method.
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cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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NMPC-based Unified Posture Manipulation and Thrust Vectoring for Agile and Fault-Tolerant Flight of a Morphing Aerial Robot
A nonlinear model predictive controller, tested in high-fidelity simulation, lets the M4 morphing robot recover from a fully failed rotor by reconfiguring its legs and remaining thrusters.