SBIR/STTR Research Award

SBIR Phase II: Robotic System for the Sorting of Recyclable Waste

Award identifier 4a9d1cda24cd2ae9c773a2bdaf39f9a816039ea8e0f0ff032959e661b3c5b1f7Awarding agency National Science Foundation

Award amount

$738,612

Program and phase

SBIR · Phase II

Award year

2016

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
COGNITIVE ROBOTICS LLC
Proposal award date
2016-04-15
Contract end date
2018-03-31
UEI
TGL1CKXT7BL5
Solicitation number
Not reported
Topic code
EW

Research abstract

The broader impact/commercial potential of this project will be to change the fundamental economics of the recycling process. Although it is estimated that up to 95% of the waste stream could be recycled, only a third of the 250 million tons of municipal solid waste that are generated each year in the United States is currently diverted. Greater diversion would provide immense savings in landfill and processing costs, and benefit the environment as well. Tens of millions of pounds of greenhouse gas emissions from virgin material mining may be eliminated, and pollution from landfill waste reduced. The existing sorting process is expensive and unprofitable, requiring human workers to manually sort debris, an extremely dull, dirty, and dangerous profession. This innovation has the potential to eliminate these trade-offs between cost and environmental damage. This Small Business Innovation Research (SBIR) Phase 2 project will create a scalable, integrated robotic system that autonomously sorts material for recycling. This advance in autonomous systems is made possible by a series of innovations in robotics: (1) tremendous improvements in both computer vision and robotic manipulation, allowing for the system to be deployed with virtually zero retrofitting in existing facilities; (2) new motion planning techniques that allow for trajectories to be generated in real time, customized for the characteristics of the waste, safety, and any uncertainty in individual objects? position;
 and (3) modern machine learning techniques that allow the system to classify waste at levels approaching human performance, with a continual training signal obtained via human supervision. These innovations pave the way for a new era in recycling, where waste is sorted cheaply, safely, and reliably on a universal scale.

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.

Research funding history

2 SBIR/STTR records share this UEI (2015–2016). Reported award amounts total $888,612. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

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