Dear Colleagues,

The increasing number of commercial applications in the aeronautic segment and the proposals of ambitious programs by national space agencies are boosting the rise of autonomous aerospace systems. A growing number of future spacecraft (S/C) are expected to operate autonomously in highly uncertain environments to enable novel mission concepts, while on Earth, unmanned aerial vehicles (UAVs) will be tasked with operating autonomously in complex and overpopulated urban environments to deliver commercial goods or emergency medical supplies, monitor traffic, etc., while avoiding collisions and granting the maximum economical return. The capability of designing a safe yet optimal control policy under significant uncertainty is thus paramount. Traditional optimal control methods based on direct or indirect methods represent consolidated tools to plan a deterministic trajectory, but a significant leap is expected to be taken in the next few years to address the forthcoming challenges in terms of performance, trustworthiness, and safety.

Convex optimization has increasingly gained popularity among the aerospace community in the last several decades, overcoming traditional methods for the solution of optimal control problems. The main factors driving this trend have been the availability of powerful interior-point algorithms for the solution of convex problems in polynomial time, theoretically sound proofs of convergence, and the rise of convexification techniques that make it possible to solve originally nonlinear problems through convex optimization algorithms. When paired with model predictive control (MPC), convex optimization makes it possible to set up a computationally efficient real-time guidance framework capable of ensuring that the flight trajectory will respect all mission constraints, be robust to model uncertainties and external disturbances, and maximize the mission performance.

This Special Issue intends to bring recognition to significant trends and novel applications of convex optimization in the field of the guidance and control of aerospace systems. Despite all these advances, several topics remain under investigation. A first area of interest concerns the development of novel lossless or successive convexification techniques to enable and expand the classes of problems that can be solved by convex optimization. A second area of interest concerns the investigation of modern and efficient discretization strategies that allow for accounting for bang–off–bang control structures. Third, reports and analyses of hardware-in-the-loop and in-flight tests that confirm the validity of embedded convex solutions for computational guidance would greatly increase the attention of private companies toward this topic.

This Special Issue thus welcomes all contributions willing to apply convex optimization methodology to aerospace problems in areas including but not limited to:

• Ascent trajectory optimization;
• Space trajectory optimization;
• Reusable launch vehicle landing;
• Spacecraft hypersonic reentry;
• Planetary or asteroid landing trajectories;
• Spacecraft rendezvous and docking;
• Drone and UAV trajectories;
• Path planning for fixed-wing and quadrotor vehicles;
• Landing and/or take-off runway optimization;
• Robotic devices for exploration;
• Ad-hoc methods for solving convex problems in real-time applications.

Dr. Alessandro Zavoli
Guest Editor

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• convex optimization
• optimal control
• space trajectory
• obstacle avoidance
• ascent trajectory
• path planning
• urban air mobility