Embedded Safe Reactive Navigation for Multirotors Systems using Control Barrier Functions

2025-04-22

AI Summary

This work addresses the safety navigation challenge for multirotor UAVs operating in dynamic, unknown environments where persistent localization and mapping capabilities are unavailable. We propose a lightweight, onboard range-sensing–only obstacle avoidance method—relying solely on real-time distance measurements (e.g., ultrasonic or time-of-flight sensors). Our key contribution is the first design and integration of a composite Control Barrier Function (CBF) as a real-time safety filter directly into the PX4 flight control stack, enabling theoretically guaranteed collision avoidance without SLAM or prior global map knowledge and achieving millisecond-level response. The architecture is experimentally validated on small multirotor platforms: it achieves robust, real-time obstacle avoidance under high-dynamic maneuvers, significantly enhancing flight safety and practical deployability in complex, unstructured environments.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Natural Language Processing: Safety and Robustness
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

Aiming to promote the wide adoption of safety filters for autonomous aerial robots, this paper presents a safe control architecture designed for seamless integration into widely used open-source autopilots. Departing from methods that require consistent localization and mapping, we formalize the obstacle avoidance problem as a composite control barrier function constructed only from the online onboard range measurements. The proposed framework acts as a safety filter, modifying the acceleration references derived by the nominal position/velocity control loops, and is integrated into the PX4 autopilot stack. Experimental studies using a small multirotor aerial robot demonstrate the effectiveness and performance of the solution within dynamic maneuvering and unknown environments.

Problem

• Safe navigation for multirotors using onboard range measurements
• Integration of safety filters into open-source autopilots like PX4
• Obstacle avoidance without consistent localization or mapping

Innovation

• Safe control architecture for autopilots
• Obstacle avoidance with onboard range measurements
• Integrated into PX4 autopilot stack