Impact-Aware Model Predictive Control for UAV Landing on a Heaving Platform
For UAV landing on heaving marine platforms, this method significantly reduces rebound and improves robustness.
This paper develops an impact-aware Model Predictive Control (MPC) framework that models landing as a velocity-level rigid-body impact using Newton's restitution law, embedded as a linear complementarity problem. Experiments show an 86.2% reduction in post-impact deflection compared to a tracking MPC.
Landing UAVs on heaving marine platforms is challenging because relative vertical motion can generate large impact forces and cause rebound on touchdown. To address this, we develop an impact-aware Model Predictive Control (MPC) framework that models landing as a velocity-level rigid-body impact governed by Newton's restitution law. We embed this as a linear complementarity problem (LCP) within the MPC dynamics to predict the discontinuous post-impact velocity and suppress rebound. In simulation, restitution-aware prediction reduces pre-impact relative velocity and improves landing robustness. Experiments on a heaving-deck testbed show an 86.2% reduction in post-impact deflection compared to a tracking MPC.