Development of An Autonomous Bridge Deck Inspection Robotic System
This addresses the inefficiency and safety concerns of manual bridge inspections for public infrastructure maintenance, though it is incremental as it applies existing robotics and sensors to a specific domain.
The authors developed an autonomous robotic system for bridge deck inspection that integrates nondestructive evaluation sensors and a navigation control algorithm to collect visual images and measurements, reducing the cost and time of data collection and inspection, and it has been deployed on numerous bridges in over ten U.S. states.
The threat to safety of aging bridges has been recognized as a critical concern to the general public due to the poor condition of many bridges in the U.S. Currently, the bridge inspection is conducted manually, and it is not efficient to identify bridge condition deterioration in order to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report a new development of the autonomous mobile robotic system for bridge deck inspection and evaluation. The robot is integrated with several nondestructive evaluation (NDE) sensors and a navigation control algorithm to allow it to accurately and autonomously maneuver on the bridge deck to collect visual images and conduct NDE measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection and inspection. For efficient bridge deck monitoring, the crack detection algorithm to build the deck crack map is presented in detail. The impact-echo (IE), ultrasonic surface waves (USW) and electrical resistivity (ER) data collected by the robot are analyzed to generate the delamination, concrete elastic modulus, corrosion maps of the bridge deck, respectively. The presented robotic system has been successfully deployed to inspect numerous bridges in more than ten different states in the U.S.