Control Barrier Functions with Audio Risk Awareness for Robot Safe Navigation on Construction Sites

📅 2026-02-12
📈 Citations: 0
✨ Influential: 0
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Technology Category

Intelligent Robots: Multimodal Perception & Sensor FusionNatural Language Processing: Safety and RobustnessPlanning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

Responsible Web: Machine-in-the-loop, human agency and autonomySecurity and Privacy: Large-scale security measurementsSystems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
📝 Abstract
Construction automation increasingly requires autonomous mobile robots, yet robust autonomy remains challenging on construction sites. These environments are dynamic and often visually occluded, which complicates perception and navigation. In this context, valuable information from audio sources remains underutilized in most autonomy stacks. This work presents a control barrier function (CBF)-based safety filter that provides safety guarantees for obstacle avoidance while adapting safety margins during navigation using an audio-derived risk cue. The proposed framework augments the CBF with a lightweight, real-time jackhammer detector based on signal envelope and periodicity. Its output serves as an exogenous risk that is directly enforced in the controller by modulating the barrier function. The approach is evaluated in simulation with two CBF formulations (circular and goal-aligned elliptical) with a unicycle robot navigating a cluttered construction environment. Results show that the CBF safety filter eliminates safety violations across all trials while reaching the target in 40.2% (circular) vs. 76.5% (elliptical), as the elliptical formulation better avoids deadlock. This integration of audio perception into a CBF-based controller demonstrates a pathway toward richer multimodal safety reasoning in autonomous robots for safety-critical and dynamic environments.
Problem

Research questions and friction points this paper is trying to address.

construction sites
robot safe navigation
audio perception
obstacle avoidance
safety-critical environments
Innovation

Methods, ideas, or system contributions that make the work stand out.

Control Barrier Functions
Audio Risk Awareness
Construction Site Navigation
Multimodal Perception
Real-time Sound Detection
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J
Johannes Mootz
Department of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, CA, United States; and Department of Mechanical and Aerospace Engineering, UC San Diego, San Diego, CA, United States
Reza Akhavian
Reza Akhavian
Associate Professor, San Diego State University
Construction RoboticsArtificial IntelligenceFuture of WorkDigital TransformationInterdisciplinary Education