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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Stanford University |
| Country | United States |
| Start Date | Feb 01, 2024 |
| End Date | Jan 31, 2026 |
| Duration | 730 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2345769 |
The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is the ability to inspect millions of miles of pipes that form critical infrastructure in both the public and private sectors. These pipes are buried under cities, are elevated across continents, and snake across factories, refineries, and treatment facilities -- transporting millions of tons of materials each day.
But these pipes are difficult to inspect and thus prone to catastrophic failure, leading to hundreds of deaths, thousands of injuries, profound environmental impact, and $7.5 billion in damages in the U.S. oil and gas industry alone from 1986 to 2013. The global market for in-pipe inspection robots is projected to exceed $2 billion in the next several years, despite the significant limitations of current products, which cannot traverse complex and tortuous pipe systems or long distances between access points.
This project will result in novel Vine Robots for nondestructive access to the interior of pipes for inspection, repair, and clog removal. The science and technology of soft robot propulsion, steering, and payload carrying will be developed to address navigation challenges that have thus far limited the effectiveness and adoption of robotic inspection.
The proposed project will make key scientific discoveries and solve practical engineering challenges required to bring soft robotics out of the research lab to solve the unmet needs of a critical real-world application, pipe inspection. Research objectives include: (1) improving Vine Robot navigation via pressure-driven eversion using workspace analysis and modeling, base station design, materials selection, and tip-steering mechanisms; (2) enabling data collection and usability during pipe navigation, by employing teleoperated and autonomous control strategies and acquisition and visualization of video and other sensor data; (3) enabling debris sampling and removal through enhanced pushing/pulling forces and payload carrying abilities; and (4) designing, fabricating, and evaluating physical Vine Robots in achieving specific performance metrics for navigating long, tortuous, and branching pipes while operated by novices and continuously acquiring in-pipe video.
Advances in soft robots will be made in material selection and design, modeling and analysis and their interaction with the environment. Novel mechanisms will be developed to create a robust and effective tip mount for a class of robot whose material at the tip is constantly changing. Finally, user friendly human-machine interfaces for visualization and interpretation of acquired data will be integrated with the Vine Robot system.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Stanford University
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