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1. Flying-Climbing Mobile Robot for Steel Bridge Inspection

   https://doi.org/10.1109/SSRR53300.2021.9597676  

   Pham, Anh Q. ; La, Anh T. ; Chang, Ethan ; La, Hung M. ( October 2021 , 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR))

   The research of robots to assist people in inspecting the quality of steel bridges has attracted significant attention in recent years. However, the intricate structure of the steel bridge components poses a massive challenge for researchers to move the robot across the bridge to perform the tests. This paper presents a new development of a hybrid flying-climbing robotic system, which can move flexibly and quickly to different positions on the steel bridge. In addition to using high-resolution cameras for an overview, the design allows the robot to stick to steel surfaces and act as a mobile robot for more detailed inspection with our developed giant magneto-resistance (GMR) sensor array system. We conduct a mechanical analysis to show the climbing capability of the mobile part. Additionally, we develop a landing algorithm to allow the robot to land on a steel surface to perform in-depth inspection safely. The designed GMR sensor array has shown the capability of detecting steel cracks to support the in-depth inspection mode. We have tested and validated our developed robot on real bridges to ensure that the design works well and is stable. 

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2. Design of A High Strength Multi-Steering Climbing Robot for Steel Bridge Inspection

   https://doi.org/10.1109/SII52469.2022.9708750  

   Motley, Cadence ; Nguyen, Son T. ; La, Hung M. ( January 2022 , 2022 IEEE/SICE International Symposium on System Integration (SII))

   The Advanced Robotics and Automation (ARA) Lab has engineered its next-generation robot for steel bridge inspection. This particular design is specialized for its particularly high strength adhesion force and high maneuverability. The robot can utilize various steering configurations such as Ackermann, synchronous and static point steering while navigating steel structures and adhering to cylindrical members. The adhesion system creates a comprehensive platform for adding extra sensing equipment by the user and will serve as a basis for future works. This paper will discuss in detail the design work done to ensure that the proposed robot would function as intended before we made it and show how the capabilities we engineered the proposed robot have made it a step forward for the steel inspection industry. 

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3. Development of a Steel Bridge Climbing Robot

   https://doi.org/10.1109/IROS40897.2019.8967748  

   Nguyen, Son Thanh ; La, Hung Manh ( November 2019 , 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

   Motivated by a high demand for automated inspection of civil infrastructure, this work presents an efficient design and development of a tank-like robot for structural health monitoring. Unlike most existing magnetic wheeled mobile robot designs, which may be suitable for climbing on flat steel surface, our proposed tank-like robot design uses reciprocating mechanism and roller-chains to make it capable of climbing on different structural shapes (e.g., cylinder, cube) with coated or non-coated steel surfaces. The developed robot is able to pass through the joints and transition from one surface to the other (e.g., from flat to curving surfaces). Taking into account several strict considerations (including tight dimension, efficient adhesion and climbing flexibility) to adapt with various shapes of steel structures, a prototype tank-like robot integrating multiple sensors (hall-effects, sonars, inertial measurement unit, Eddy current and cameras), has been developed. Rigorous analysis of robot kinematics, adhesion force, sliding failure and turn-over failure has been conducted to demonstrate the stability of the proposed design. Mechanical and magnetic force analysis together with sliding/turn-over failure investigation can serve as an useful framework for designing various steel climbing robots in the future. The robot is integrated with cameras and Eddy current sensor for visual and in-depth fatigue crack inspection of steel structures. Experimental results and field deployments confirm the adhesion, climbing, inspection capability of the developed robot. 

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4. A Practical Climbing Robot for Steel Bridge Inspection

   https://doi.org/10.1109/ICRA40945.2020.9196892  

   Nguyen, Son T. ; Pham, Anh Q. ; Motley, Cadence ; La, Hung M. ( May 2020 , 2020 IEEE International Conference on Robotics and Automation (ICRA))

   The advanced robotic and automation (ARA) lab has developed and successfully implemented a design inspired by many of the various cutting edge steel inspection robots to date. The combination of these robots concepts into a unified design came with its own set of challenges since the parameters for these features sometimes conflicted. An extensive amount of design and analysis work was performed by the ARA lab in order to find a carefully tuned balance between the implemented features on the ARA robot and general functionality. Having successfully managed to implement this conglomerate of features represents a breakthrough to the industry of steel inspection robots as the ARA lab robot is capable of traversing most complex geometries found on steel structures while still maintaining its ability to efficiently travel along these structures; a feat yet to be done until now. 

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5. Vision AI-based human-robot collaborative assembly driven by autonomous robots

   https://doi.org/10.1016/j.cirp.2024.03.004  

   Liu, Sichao ; Zhang, Jianjing ; Wang, Lihui ; Gao, Robert X ( July 2024 , CIRP Annals)

   Autonomous robots that understand human instructions can significantly enhance the efficiency in human-robot assembly operations where robotic support is needed to handle unknown objects and/or provide on-demand assistance. This paper introduces a vision AI-based method for human-robot collaborative (HRC) assembly, enabled by a large language model (LLM). Upon 3D object reconstruction and pose establishment through neural object field modelling, a visual servoing-based mobile robotic system performs object manipulation and navigation guidance to a mobile robot. The LLM model provides text-based logic reasoning and high-level control command generation for natural human-robot interactions. The effectiveness of the presented method is experimentally demonstrated. 

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