Intelligent Robotic Systems for Bridge Inspection comprehensively overviews the methods used in the development of robotic and AI-powered systems for inspection and potential defect identification of bridges (while maintaining their serviceability under inspection). The book underscores the crucial importance of monitoring structural health and operational conditions of our bridge infrastructure to assess resilience and service lifespan. Sections cover how advanced technologies in robotics and AI can offer significant advantages to a sector that requires timely, systematic reviews of this critical component of the transportation sector.
1. Introduction
2. Intelligent Bridge Inspection
3. Robotic Systems for Bridge Inspection
4. Human-Robot Collaboration for Sensor-rich Robotic Bridge Inspection
5. Heterogeneous Multi-Robot Teams for Bridge Inspection
6. Digital Twins for Bridge Inspection
7. Bridge Inspection with Intelligent Robotic Systems: Present and Future
Dr Quang Ha received the B.E. degree from Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam, in electrical engineering, and the Ph.D. degrees from Moscow Power Engineering Institute, Moscow, Russia, in complex systems and control, and the University of Tasmania, Australia, in intelligent systems. He is currently an Associate Professor with the School of Electrical and Data Engineering of the Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia. His research interests include automation, robotics, and control systems. Dr Hung Manh La is the Director of the Advanced Robotics and Automation Lab, and Associate Professor at the Department of Computer Science and Engineering, University of Nevada, Reno, NV, USA. From 2011 to 2014, he was a Post-Doctoral research fellow and then a Research Faculty Member at the Center for Advanced Infrastructure and Transportation, Rutgers University, Piscataway, NJ, USA. He has authored over 145 papers published in major journals, book chapters, and international conference proceedings. Ten of his papers have won best conference paper awards and best paper finalists in the top ranked robotics conferences (e.g., IROS2022, SII2022, IROS2019, SSRR2018, ICRA2017, ISARC2015). His current research interests include robotics, deep learning, and AI. Dr Ngai Ming Kwok received his PhD degree from the University of Technology Sydney, Australia, in 2007. He holds the position of Adjunct Fellow in the School of Engineering, Design & Built Environment at Western Sydney University, Australia. His research interests include mobile robotics, image processing, intelligent computation, wireless sensor networks and system monitoring
