SBIR/STTR Research Award

Robotic Crack Sealing for Superior Pavement Maintenance

Award identifier b1609980778ab461ddd32130f610552c4ab9a4c20542c56f8195e1ce27e2acc2Awarding agency Department of Defense · Air Force

Award amount

$749,918

Program and phase

SBIR · Phase II

Award year

2022

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
NECOTECH LLC
Proposal award date
2022-07-19
Contract end date
2023-10-25
UEI
GUBQF5JJHNH6
Solicitation number
X21.2
Topic code
AF212-CSO1

Research abstract

Asphalt is the bedrock of our nation’s transportation and logistics infrastructure. In the US alone, 85 to 90 percent of all runways at our nation's 3,364 commercial airports are surfaced with asphalt pavement. But, airfield asphalt is expensive as it requires significant upfront capital investment, constant maintenance and repair, and replacement every 15 to 20 years due to normal wear and tear, climate effects, and product lifespan.  Preservation of these pavement runways is significantly more cost effective than replacement and reconstruction. Robotic crack sealing of airbase pavements provides an effective, efficient means for extending pavement life while reducing manual labor, safety concerns and maintenance equipment needs. necoTech is acting as the catalyst to advance existing pavement technologies through the use of robotic applications adapted with an autonomous vehicle to directly support USAF runway crack sealing and pavement maintenance needs. This technology will extend the life of airbase pavement by providing an efficient, lower-cost means for routine repair of cracks and damage as it occurs. necoTech is dedicated to reducing the overall footprint of necessary infrastructure repair and construction, including the evolution of machinery and equipment. Our approach represents the convergence of existing, standard infrastructure repair technologies with machine learning technologies that result in higher-quality application with less waste and less reliance on human labor. We hold a DoD license to pursue the development of robotic technologies for use in aerospace applications. Our planned approach is to mount a robotic arm on a traditional truck chassis. Using AI, this robotic technology uses the following procedure for crack repair: Laser Identification of existing pavement crack using Machine Learning (ML) Upon affirmative crack identification, the robot will blow debris out of the crack, preparing it for crack sealing material. Using AI, apply prepared crack sealing materials with better material control currently available in the industry. In addition to providing better quality and longer lasting crack sealing, our technology offers efficiencies not currently found in the industry.  As envisioned, our application is capable of repairing a half mile an hour on a four-lane road, twice as fast as the industry standard.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

15 SBIR/STTR records share this UEI (2020–2024). Reported award amounts total $3,306,790. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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