Quadrotor safety improved by torque-level control with nonlinear dynamics

Safety-Critical Quadrotor Navigation Using Fourth-Order Control Barrier Functions with Full Nonlinear Quadrotor Dynamics

Robotics

Summary

Flying quadrotor drones safely around obstacles is tricky because their flight controllers usually handle position and attitude separately, which can cause problems in tight spaces. This paper presents a new safety controller that manages the drone’s full complex motion—including how it tilts and uses its motors—to avoid crashes more effectively. By combining advanced math called fourth-order control barrier functions, the method directly controls torque and drone attitude, improving safety without relying on separate steps. The authors tested their approach in simulations and real flights, showing it can reliably keep drones away from obstacles.

What this means in practice

  • For drone flight system engineers: Integrate torque-level safety control that accounts for full nonlinear quadrotor dynamics to improve obstacle avoidance and flight reliability.
  • For robotics hardware developers: Develop drone control hardware and firmware that support high-order control barrier functions for safer navigation in cluttered environments.

Authors

Yanze Liu, Yaşar İdikut, Dhruv Madhusudan Agrawal, Wei Xiao, Guanrui Li

Abstract

Safety-critical quadrotor navigation in cluttered environments typically relies on hierarchical architectures in which a high-level safety filter modifies position references that are then tracked by a separate attitude controller. However, this separation can create a mismatch between translational safety objectives and attitude evolution. To address this gap, we propose a safety controller based on fourth-order control barrier functions (CBFs) that explicitly incorporates the full nonlinear quadrotor dynamics, including attitude dynamics and torque-level actuation. Furthermore, we apply the integral high-order CBF technique to resolve the mixed-relative degree issue in the derived constraint formulation. The resulting formulation enforces obstacle-avoidance constraints while optimizing control torques, granting the safety layer direct authority over attitude behavior and eliminating the hierarchical disconnect inherent in reference-tracking safety filters. We validate the approaches in both high-fidelity simulation and real-world flight experiments, demonstrating reliable constraint satisfaction and successful obstacle avoidance. These results suggest that torque-level high-order CBFs provide a practical pathway to provably safer quadrotor navigation under full rigid-body dynamics.
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