New algorithm enables drones to land themselves in real time
Researchers have developed an optimization algorithm that solves complex control problems fast enough for autonomous drones to make landing decisions in real time. The breakthrough, tested on actual aircraft, could accelerate adoption of autonomous systems in delivery, inspection, and emergency response operations where split-second decisions are critical.
Originaltitel: An optimization algorithm based on forward recursion with applications to variable horizon MPC
<p>We consider optimization algorithms designed for variable horizon model predictive control. Traditionally, such problems are considered intractable for real-time applications that require fast computations, as they need to solve multiple optimal control problems with varying horizons at each sampling instance. The main contribution is an algorithm that efficiently solves multiple optimal control problems with different prediction horizons in a recursive manner. This algorithm has been successfully implemented and integrated into the OSQP solver, resulting in a real-time controller that is both fast and reliable. To assess the effectiveness of the approach, we conducted evaluations in both a realistic simulation environment and on real hardware during outdoor flight experiments. Specifically, we focused on two distinct rendezvous maneuvers for autonomous landings of unmanned aerial vehicles. The results obtained from these evaluations further validate the practicality and efficacy of the proposed algorithm. (c) 2023 The Author(s). Published by Elsevier Ltd on behalf of European Control Association. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )</p>