SBIR/STTR Research Award

SBIR Phase II:Automated Perception for Robotic Chopsticks Manipulating Small and Large Objects in Constrained Spaces

Award identifier f9e5bc2ec7f79ea78e308e421ebdde29a376515ebd544a4d97abe2605680c3c3Awarding agency National Science Foundation

Award amount

$999,746

Program and phase

SBIR · Phase II

Award year

2023

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
DEXTROUS ROBOTICS, INC.
Proposal award date
2023-10-01
Contract end date
2025-09-30
UEI
MD44UJ6AZMP5
Solicitation number
NSF 23-516
Topic code
R

Research abstract

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project supports the development of robotic solutions for unloading non-palletized packages of different shapes and sizes in logistics and similar industries.This technology may provide workers with more skilled jobs that remove the need for physically strenuous labor in unhealthy environments. The project seeks to increase US competitiveness in supply chain logistics ($150 billion / year market in the US) by helping solve long-standing and worsening employee recruitment and retention problems. The project helps the US become an early leader in the robotic manipulation of diverse objects in constrained, unstructured environments while simultaneously training a workforce capable of remote manipulation in safe environments._x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase II project supports the development of robotic solutions for unloading non-palletized packages of different shapes and sizes in logistics and similar industries. At present, there are few commercially-available automated solutions for this task. Those few machines are brittle, slow, and only work well with uniform packages. The research objectives include: 1) upgrading the robot’s perception system to fuse high-speed vision and force sensory inputs, which will enable closed-loop picking with greater speed, more robustness, higher safety, and less package damage; 2) upgrading the robot’s vision system to perceive object categories beyond boxes; 3) investigating a user interface to allow a human operator to most-easily correct inevitable perception system errors; and 4) field testing the roboticsystem. The cumulative result will be a rigorously validated system that safely (for packages and users) operates at high speed with little manual intervention._x000D_ _x000D_ 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.

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 (2021–2023). Reported award amounts total $1,255,746. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.