Feasibility and Singularity in High-Order Safety-Critical Control for Quadrotor UAVs

2026-09-16

AI Summary

研究了在输入受限和避碰约束下四旋翼无人机团队的高阶安全关键控制问题，通过扭矩感知动态扩展和高斯过程学习方法提高控制有效性与安全性。

Abstract

We study high-order safety-critical control of quadrotor teams under bounded inputs and pairwise collision-avoidance constraints. Squared-distance barriers may lose thrust effectiveness when the relative displacement is orthogonal to the available thrust directions, while nonsingular constraints may still be jointly infeasible under shared bounds. We characterize both phenomena through pairwise effectiveness and aggregate feasibility measures. A torque-aware dynamic extension exposes attitude torques in a fourth-order barrier and prevents the extended-input row from vanishing under positive thrust. Gaussian processes directly learn the fourth-order HOCBF residual, providing robust margins without differentiating unknown perturbations. Under residual-bound and persistent-feasibility assumptions, the resulting QP guarantees collision avoidance and recovers the nominal input whenever it satisfies the robust safety and actuator constraints.

Problem

• quadrotor UAVs
• high-order safety-critical control
• collision-avoidance
• bounded inputs
• thrust effectiveness

Innovation

• torque-aware dynamic extension
• Gaussian processes
• fourth-order HOCBF