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SBIR Phase I: Robotic vertical glass sorter powered by machine vision and artificial intelligence for accurate, accessible, sustainable, and cost-effective glass recycling

SBIR Phase I: Robotic vertical glass sorter powered by machine vision and artificial intelligence for accurate, accessible, sustainable, and cost-effective glass recycling
SBIR 第一阶段:由机器视觉和人工智能驱动的机器人垂直玻璃分类机,可实现准确、可访问、可持续且经济高效的玻璃回收
批准号:
2105995
负责人:
Parag Tandon
金额:
$25.56万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-08-01 至 2023-06-30

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中文摘要
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英文摘要
The broader impact of this Small Business Innovation Research (SBIR) Phase I project will address the over 10 million metric tons of glass disposed of annually in the U.S. While 100% of glass is recyclable, only 33% is actually recycled, as it is challenging to sorting and transport used glass prior to recycling. Traditional methods for these key functions dramatically reduce the value of the glass due to transportation costs and required warehouse space for sorting glass from other waste and separate the colors of clear, brown, and green. Even modern U.S. glass sorting facilities require warehouse space of more than 250,000 square feet for horizontal runway and belt systems to clean and sort waste streams well enough for an automated glass sorter to continue. This leads to high costs, manual labor, negative environmental impact for the machines, and high levels of glass that is not recycled. The proposed project advances a robotic system to sort efficiently. This Small Business Innovation Research Phase I project will target a prototype hopper and actuator control system, AI engine for detection and sorting, and field performance study. The main development challenges include enhancing the camera and sensor network of the prototype platform; developing and validating an AI engine for rapid classification of falling glass; and developing actuator controls, and system integration and functional testing to specifications. First, the prototype will be enhanced including the mechanical design, material flow, sensor network, and actuators for the sorting mechanisms. Next, using prerecorded videos of falling glass and waste under different conditions, an AI engine will be developed and validated to accurately classify glass colors and trigger an actuator sequence. Once algorithms have been validated offline, the hardware and algorithms will be integrated at a system level and validated for performance in real-time operation.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.
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