Abstract
This report presents the development and implementation of autonomous navigation systems for steel bridge inspection robots, designed to enhance the efficiency and safety of bridge maintenance. The Advanced Robotics and Automation (ARA) lab has developed innovative climbing robots capable of operating in complex environments using a hybrid approach that combines mobile and inch-worm-inspired locomotion modes. A novel control and navigation framework has been proposed, featuring algorithms for surface detection, path planning, and mode switching based on 3D point cloud data. The effectiveness of these systems has been validated through experiments on steel bridge structures, demonstrating the potential for real-world application in autonomous bridge inspections, significantly reducing the need for human intervention.
Recommended Citation
La, Hung Manh, "Final Report - Nondestructive Data Driven Motion Planning for Inspection Robots" (2024). Project AS-5. 1.
https://scholarsmine.mst.edu/project_as-5/1
Department(s)
Civil, Architectural and Environmental Engineering
Research Center/Lab(s)
INSPIRE - University Transportation Center
Sponsor(s)
Office of the Assistant Secretary for Research and Technology U.S. Department of Transportation 1200 New Jersey Avenue, SE Washington, DC 20590
Keywords and Phrases
Climbing robot, autonomous inspection, localization, motion planning
Report Number
INSPIRE-022
Document Type
Technical Report
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2025 Missouri University of Science and Technology, All rights reserved.
Publication Date
August 16, 2024
Comments
Principal Investigator: Hung Manh La, Ph. D.
Grant #: USDOT # 69A3551747126
Grant Period: 11/30/2016 - 09/30/2024
Project Period: 01/01/2019 - 06/30/2024
The investigation was conducted under the auspices of the INSPIRE University Transportation Center.