Simulation Training to Work with Bridge Inspection Robots
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Description
This project aims to investigate and develop a Simulation Training and Control System (STACS) that helps bridge inspectors equipped with virtual or augmented reality hardware to work together with semi-autonomous and autonomous robots to efficiently and effectively inspect bridge trusses more thoroughly and in less time. Our efforts to date have resulted in a simulation training system for bridge inspection enabling a heterogeneous group of simulated robots to speed up comprehensive bridge inspection.
The PI will investigate and develop techniques to 1) Move STACS towards a Virtual Reality (VR) interface for training and control, 2) connect simulated robots with real robots being developed in other INSPIRE projects, and 3) investigate and develop algorithms, protocols, and autonomy for maximizing inspection speed and completeness for human-robot bridge inspection teams on real bridges.
The same system and command interfaces are being used for training human bridge operators in simulation and in an operational environment. We thus expect a straightforward transition from simulation training to on-site operation as the DOT moves to leverage our system’s AI and autonomy development to increase safety and reduce cost. We expect to provide and disseminate a prototype XRSTACS system. The system will feature automated route generation, connectivity to at least two types of robots, and enable multiple views of robots’ task achieving progress. XR-STACS will be publicly available on Github and on the INSPIRE site.
Presentation Date
11 Aug 2021, 11:00 am - 11:30 am
Meeting Name
INSPIRE-UTC 2021 Annual Meeting
Department(s)
Civil, Architectural and Environmental Engineering
Document Type
Presentation
Document Version
Final Version
File Type
text
Language(s)
English
Simulation Training to Work with Bridge Inspection Robots
This project aims to investigate and develop a Simulation Training and Control System (STACS) that helps bridge inspectors equipped with virtual or augmented reality hardware to work together with semi-autonomous and autonomous robots to efficiently and effectively inspect bridge trusses more thoroughly and in less time. Our efforts to date have resulted in a simulation training system for bridge inspection enabling a heterogeneous group of simulated robots to speed up comprehensive bridge inspection.
The PI will investigate and develop techniques to 1) Move STACS towards a Virtual Reality (VR) interface for training and control, 2) connect simulated robots with real robots being developed in other INSPIRE projects, and 3) investigate and develop algorithms, protocols, and autonomy for maximizing inspection speed and completeness for human-robot bridge inspection teams on real bridges.
The same system and command interfaces are being used for training human bridge operators in simulation and in an operational environment. We thus expect a straightforward transition from simulation training to on-site operation as the DOT moves to leverage our system’s AI and autonomy development to increase safety and reduce cost. We expect to provide and disseminate a prototype XRSTACS system. The system will feature automated route generation, connectivity to at least two types of robots, and enable multiple views of robots’ task achieving progress. XR-STACS will be publicly available on Github and on the INSPIRE site.
