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April 12, 2026Remote Sensing0 citationsOpen Access

Integrated Air–Ground Robotic System for Autonomous Post-Blast Operations in GNSS-Denied Tunnels

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GAGoretti Arias-FerreiroMMMarco A. Montes-GrovaFPFrancisco J. Pérez-Grau

Key Points

  • The aim is to develop a system that automates post-blast operations in tunnels while minimizing risks posed to human workers.
  • Developed an integrated cyber-physical system with UAV and AWL.
  • Utilized a Digital Twin as the central interface for coordination.
  • Validated technology in a GNSS-denied tunnel environment.
  • Evaluated post-blasting conditions collaboratively between aerial and ground agents.
  • UAV mapped excavation front in under 8 minutes.
  • Operational commencement was 50% to 80% faster than manual methods.
  • Reduced daily operational time by approximately 8%.
  • Estimated return on investment within one to seven months.

Abstract

Post-blast operations in tunnel construction represent a critical bottleneck due to mandatory downtime and hazardous environmental conditions. This study addresses these challenges by developing and validating an integrated cyber–physical architecture that coordinates an autonomous Unmanned Aerial Vehicle (UAV) and an Autonomous Wheel Loader (AWL) under the supervision of a Digital Twin acting as central operational digital interface. Specifically, this technology was designed to access the tunnel, evaluate post-blasting conditions, and initiate operations during mandatory exclusion periods for personnel. The system was validated in a realistic, Global Navigation Satellite System (GNSS)-denied tunnel environment emulating post-detonation visibility constraints. The results demonstrate that the aerial agent successfully navigated and mapped the excavation front in less than 8 min, establishing a shared coordinate system for the ground machinery. Through this collaborative workflow, the autonomous deployment enabled operations to commence 50% to 80% earlier than conventional manual procedures. Furthermore, the system reduced daily operational time by approximately 8%, with an estimated return on financial investment between one and seven months. Overall, the proposed framework eliminates human exposure during high-risk inspections and transforms the fragmented excavation cycle into a continuous, data-driven process.

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Cite This Study

Arias-Ferreiro et al. (2026) studied this question.

synapsesocial.com/papers/69db383b4fe01fead37c6780https://doi.org/10.3390/rs18081133
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