Design of a Multi‐Sensor Integrated Control System for Vehicle‐Mounted Tunnel Lining Inspection With Real‐Time Velocity and Posture Tracking

ABSTRACT This study presents a holistically integrated multi‐sensor control system for vehicle‐mounted tunnel lining inspection, seamlessly combining Automated Track Vehicle (ATV) technology with robotic‐arm posture tracking within a synergistic framework. The system achieves automated velocity regulation and millimeter‐level positioning accuracy, significantly enhancing inspection efficiency and operational safety. Key innovations include: (1) a coupled kinematic/dynamic model of the vehicle‐arm system to capture motion coupling effects; (2) an optimized feedback control architecture incorporating an Auto‐Disturbance Rejection Controller (ADRC) with detailed design, tuning, and stability analysis; (3) real‐time data transmission via industrial Ethernet and the Modbus/TCP protocol (with average latency 1.54 ms, ≤ 2 ms); (4) a multi‐sensor fusion logic based on extended Kalman filter (EKF) for dynamic posture correction. Experimental validation confirms that the system maintains a dynamic deviation of ≤ 8 mm/s at operational speeds of 1–5 km/h, keeps the antenna‐to‐lining distance at 100 ± 20 mm, and ensures Ground Penetrating Radar (GPR) signal integrity at standoff distances ≤ 0.25 m. This research establishes a robust technological foundation for next‐generation autonomous tunnel inspection systems and represents a significant advancement in the robustness of non‐destructive testing methodologies for critical infrastructure.

Authors

Institutions

Publication Details

Journal
Journal of Field Robotics
Published
2026-01-15
DOI
https://doi.org/10.1002/rob.70164
Primary Topic
Robotic Locomotion and Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design of a Multi‐Sensor Integrated Control System for Vehicle‐Mounted Tunnel Lining Inspection With Real‐Time Velocity and Posture Tracking

Qing Yuan Zhou, Jianli Zhao, Tian Zhang, Tian Tian et al.
Journal of Field Robotics
Robotic Locomotion and Control
article

Design of a Multi‐Sensor Integrated Control System for Vehicle‐Mounted Tunnel Lining Inspection With Real‐Time Velocity and Posture Tracking

Qing Yuan Zhou, Jianli Zhao, Tian Zhang, Tian Tian, Lei Yang, Falin Qi, Kai Pan, Xiaoli Ju, Feiyu Jia, Bo Jiang, Xiaoxiao Liu
article en

Abstract

ABSTRACT This study presents a holistically integrated multi‐sensor control system for vehicle‐mounted tunnel lining inspection, seamlessly combining Automated Track Vehicle (ATV) technology with robotic‐arm posture tracking within a synergistic framework. The system achieves automated velocity regulation and millimeter‐level positioning accuracy, significantly enhancing inspection efficiency and operational safety. Key innovations include: (1) a coupled kinematic/dynamic model of the vehicle‐arm system to capture motion coupling effects; (2) an optimized feedback control architecture incorporating an Auto‐Disturbance Rejection Controller (ADRC) with detailed design, tuning, and stability analysis; (3) real‐time data transmission via industrial Ethernet and the Modbus/TCP protocol (with average latency 1.54 ms, ≤ 2 ms); (4) a multi‐sensor fusion logic based on extended Kalman filter (EKF) for dynamic posture correction. Experimental validation confirms that the system maintains a dynamic deviation of ≤ 8 mm/s at operational speeds of 1–5 km/h, keeps the antenna‐to‐lining distance at 100 ± 20 mm, and ensures Ground Penetrating Radar (GPR) signal integrity at standoff distances ≤ 0.25 m. This research establishes a robust technological foundation for next‐generation autonomous tunnel inspection systems and represents a significant advancement in the robustness of non‐destructive testing methodologies for critical infrastructure.

Journal of Field Robotics
China Electric Equipment Group (China) (CN), Taiyuan Heavy Industry (China) (CN), China Academy of Railway Sciences (CN), Jiangsu University of Technology (CN), Beijing Building Construction Research Institute (China) (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 87%
Robotic Locomotion and Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.