Climbing Robots with Automated Deployment of Sensors and NDE Devices for Steel Bridge Inspection

The PI was a research scientist/faculty at Rutgers University who successfully developed in 2014 a Robotic Assisted Bridge Inspection Tool (RABIT) for bridge deck inspections. Other bridge elements, such as girders and columns, or even underside of bridge decks are difficult to access and remain a challenge for efficient inspection. Like visual inspection, current practices for bridge maintenance are equally time consuming and expensive. Automation of simple maintenance actions such as bearing cleaning and concrete sealing with robots will lead to a leap forward to the next-generation strategy of bridge maintenance. This project aims to develop and prototype automated climbing robotic platforms for steel bridge inspection and evaluation with support of visual and 3D LiDAR for navigation in global positioning system (GPS)-denied environments, develop a nondestructive evaluation (NDE) device or sensors deployment strategy with a mechanical limb, and evaluate the condition of steel bridges based on data collected from the device or sensors

Climbing Robots for Steel Bridge Inspection and Evaluation

Steel structures and steel bridges, constituting a major part in civil infrastructure, require adequate maintenance and health monitoring. In the U.S., more than 50,000 steel bridges are either deficient or functionally obsolete, which likely presents a growing threat to people\u27s safety. The collapse of numerous bridges recorded over the past 16 years has shown significant impact on the safety of all travelers. In this presentation, the design and implementation of two different climbing robots for steel structure inspection are reported. Based on the magnetic wheel design, the robot can climb on different steel surface structures (i.e., flat, cylinder, cube). The robots can be remotely controlled or programmed to move autonomously on steel structures. Current tests shows that the robots can carry up to 8 pounds of load while being able to adhere strongly on the steel surface. Climbing capability tests are done on bridges and on several steel structures with coated or unclean surfaces. Although the steel surface is curved and rusty, the robots can still adhere tightly

Roller Chain-Like Robot for Steel Bridge Inspection

This paper presents a novel design of steel bridge/structure inspection robot. Compared to most existing robots designed to work on particular surface contour of steel structures such as flat or curving, the proposed roller chain-like robot can implement and transfer smoothly on many kind of steel surfaces. The developed robot can be applied to inspection tasks for steel bridges with complicated structures. The robot is able to carry cameras, sensors for visual and specialized examination. Rigorous analysis of robot kinematics, adhesion force and turn-over failure has been conducted to demonstrate the stability of the proposed design. Mechanical and magnetic force analysis together with turn-over failure investigation can serve as an useful framework for designing various steel climbing robots in the future. Experimental results and field deployments prove the adhesion, climbing, inspection capability of the developed robot

Localization and detection of wireless embeddable structural sensors using an unmanned aerial vehicle in the absence of visual markers

The objective of this thesis is to develop a fully integrated UAV based platform for autonomous collection of data from embedded sensors. Passive (battery-less) embedded sensors provide means for periodic long-term monitoring of civil structures like bridges. However, collection of data from these sensors requires extensive manual effort of locating them. UAVs can automate this process, although localization of these embedded tags in absence of visual markers pose a challenge. A RF (13.56MHz) reader is used to capture data from RF tags wirelessly. Different tag coil sizes are tested to observe effects on read range as well as to characterize the interaction volume between reader and tag. The UAV platform is integrated with the RF reader to autonomously capture data from tags using GPS based localization. Different sensor configurations are tested and characterized to meet the requirements of X,Y,Z localization set by the reader and tag interaction volume. Flight characteristics are also observed for various UAV navigation parameters. Results suggest that by using low-cost RTK GPS unit, the UAV is capable of detecting and localizing RF tags without any visual markers or aides.Electrical and Computer Engineerin

Automated robotic monitoring and inspection of steel structures and bridges

© 2018 Cambridge University Press. This paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real-time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning

Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality

Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants