Collision Avoidance and Geofencing for Fixed-wing Aircraft with Control Barrier Functions

TL;DR

This work addresses safety-critical control for fixed-wing aircraft by enforcing collision avoidance and geofencing with formal guarantees using run-time assurance (RTA) powered by control barrier functions (CBFs). It develops multiple CBF constructions—velocity-based extended CBFs, backstepping-based CBFs, and a model-free RTA—plus a composition framework to handle multiple safety constraints, all formulated for a reduced-order 3D Dubins model and validated on a high-fidelity envelope-identified model. The results show that the extended and backstepping CBFs enable full use of control inputs (acceleration, pitch, roll) to achieve safe avoidance and geofence adherence, while the model-free approach offers simplicity at the cost of larger control efforts and potential motion limitations. Overall, the proposed RTA framework provides provable safety for complex aerospace tasks and lays groundwork for handling additional envelope constraints and hardware validation in future work.

Abstract

Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, preferably with formal guarantees of safe behavior. This paper establishes the safety-critical control of fixed-wing aircraft in collision avoidance and geofencing tasks. A control framework is developed wherein a run-time assurance (RTA) system modulates the nominal flight controller of the aircraft whenever necessary to prevent it from colliding with other aircraft or crossing a boundary (geofence) in space. The RTA is formulated as a safety filter using control barrier functions (CBFs) with formal guarantees of safe behavior. CBFs are constructed and compared for a nonlinear kinematic fixed-wing aircraft model. The proposed CBF-based controllers showcase the capability of safely executing simultaneous collision avoidance and geofencing, as demonstrated by simulations on the kinematic model and a high-fidelity dynamical model.

Figures (7)

• Figure 1: Overview of the safety-critical control framework for fixed-wing aircraft. The motion of a single aircraft is controlled to avoid collisions with other aircraft and prevent crossing a geofence in 3D space. To this end, the proposed control barrier function-based run time assurance system intervenes into the nominal flight controller whenever necessary to avoid dangers.
• Figure 2: Illustration of aircraft kinematics: position coordinates $n$, $e$, $d$, Euler angles $\phi$, $\theta$, $\psi$, speed $V_{\rm T}$, angular velocities $P$, $Q$, $R$, and acceleration $A_{\rm T}$.
• Figure 3: Simulation of RTA in collision avoidance using extended CBF. The aircraft successfully maintains safety.
• Figure 4: Simulation of RTA in geofencing using extended CBF. The controller fails this task as it would command the aircraft to stop in front of the geofence. This CBF choice lacks the ability to make the aircraft turn left or right.
• Figure 5: Simulation of RTA in simultaneous collision avoidance and geofencing using backstepping-based CBF. Safety is successfully maintained by leveraging both acceleration, pitching, rolling, and turning.

Theorems & Definitions (1)

• proof