| NSF Org: |
TI Translational Impacts |
| Recipient: |
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| Initial Amendment Date: | June 3, 2020 |
| Latest Amendment Date: | June 3, 2020 |
| Award Number: | 2027693 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Anna Brady-Estevez
TI Translational Impacts TIP Directorate for Technology, Innovation, and Partnerships |
| Start Date: | June 1, 2020 |
| End Date: | May 31, 2021 (Estimated) |
| Total Intended Award Amount: | $256,000.00 |
| Total Awarded Amount to Date: | $256,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1800 S OAK ST STE 111 CHAMPAIGN IL US 61820-6974 (217)402-4767 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
60 Hazelwood Drive Champaign IL US 61820-7460 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | STTR Phase I |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.084 |
ABSTRACT
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is to respond to the COVID-19 pandemic. The proposed work will rapidly create new autonomous robots for sanitization in hospitals and other high-traffic areas with high risk of surface-borne pathogen transmission. The autonomous sanitizing system produced by this effort would fill a crucial void in ensuring hospital spaces are kept sanitized as the health care system scrambles to respond to the evolving COVID-19 crisis. In addition, the solution will be widely applicable in controlling Hospital Acquired Infections, affecting over 2 million people in the US annually, with an overall economic impact of $45 B. The proposed autonomous high-dexterity robots are projected to successfully keep the high-touch areas in about 10,000 square feet of commercial space reliably sanitized and could be applicable to the over 50 billion square feet of public commercial space (office, industrial, healthcare, hospitality, retail, etc.) in the US. Faster, more efficient, and targeted santization has potential to dramatically reduce downtime of these spaces and the labor required for sanitization.
This STTR Phase I project, in response to the ongoing COVID-19 crisis, will rapidly develop new robotic systems and algorithms for robots capable of precisely navigating surfaces in crowded environments. This new system will be capable of selective sanitization in the proximity of humans, removing the key limitation of existing full-room single-source UV radiation based robots requiring the room to be unoccupied. UV light technology has tremendous promise in improving sanitization at hospitals and reducing costs by minimizing chemical use, but the technology has had limited application due to ill effects on mammalian cells. The selective exposure capability with the use of the robotic arm and focused lighting will alleviate that limitation, opening up further uses of UV lighting in hospital sanitization. Toward this goal, this project will advance key areas of robotics, including Simultaneous Localization and Mapping (SLAM) algorithms in the presence of dynamic obstacles, and the control of arms over surfaces with varied objects and in the vicinity of humans. These efforts will advance the science and practice of robotics for applications in healthcare and other industries.
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.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project assessed the technical feasibility of a targetted robotic disinfection unit that can disinfect portions of indoor environments with ultraviolet (UV) light more efficiently than traditional methods of UV disinfection.
Although portable UV lamps and lamps mounted on movable bases have been used successfully, they have some serious drawbacks. Primarily, occlusions to the UV light are caused by furniture, equipment, handles, crevices, and even buttons and dials, causing “shadow regions” that are not disinfected much, if at all. This means that UV disinfection has so far been limited to a precautionary backup to a first-round manual disinfection by wiping and scrubbing. A second disadvantage is that UV disinfection of a room-scale environment from a central lamp is slow, requiring a room be vacated for up to an hour. This makes the technology inefficient for crisis situations. The slow operation rate is primarily due to radiant flux reduction at far distances according to the inverse square law. By bringing the UV emitter close to the surface to be disinfected, the flux needed to inactivate pathogens can be delivered in under a minute, rather than tens of minutes.
The project led to the development of a prototype mobile robot with an arm that the robot can position to disinfect high-touch surfaces in the room. The movable arm with multiple degrees of freedom ensures that there are no shadow regions left untreated, and can bring the UV light close to the surface, thereby increasing the UV dosage. Robotic perception algorithms were created to create 3-D maps of indoor environments, and to identify and prioritize high-touch areas. Using this input, planning algorithms were created to plan a path for the robot and the arm through indoor spaces. The robot was equipped with software to be able to autonomously traverse indoor environment to execute the disinfection plan.
The team is continuing to improve the autonomous object detection and disinfection algorithms, as well as UV light selection and hardware optimization. We have identified potential customers and expect to collaborate with them to evaluate the disinfection performance of the future robotic prototypes.
Last Modified: 07/30/2021
Modified by: Chinmay Soman
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