1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
This listing may be outdated. Verify details at the official source before applying.
Find similar grantsCAREER: Active Scene Understanding By and For Robot Manipulation is sponsored by National Science Foundation (NSF). This NSF CAREER award supports research focused on active scene understanding for robot manipulation.
Get a weekly digest of new grants like this
A free weekly digest of new foundation and federal funding opportunities as they're added to Granted. Unsubscribe anytime.
Or search similar grants →Extracted from the official opportunity page/RFP to help you evaluate fit faster.
Despite significant progress, most robot perception systems today remain limited to "seeing what they are asked to see" ─ detecting pre-defined categories of objects by watching static images or videos. In contrast, humans constantly decide "what to see" and "how to see it" using active exploration. This ability is central to problem-solving and adaptability to novel scenarios but remains missing from robots today.
To bridge this gap, this Faculty Early Career Development (CAREER) project aims to study a self-improving robot perception system using manipulation skills ─ referred to as active scene understanding.
The framework suggested in this project improves a robot's fundamental capabilities in perception and planning and therefore impacts many application domains such as service robots or field exploration, where robots need to rapidly analyze their environments in order to swiftly react to evolving situations.
The research and education plans are integrated through a Cloud-Enabled Robot Learning Platform, which allows students to participate in robotics education and research without the limits of robot and compute hardware accessibility. This project tackles a number of challenges in active scene understanding to achieve a unified and practical framework.
The key idea of the approach is to leverage the synergies between a robot's perception and interaction algorithms to create self-supervisory signals. On the one hand, the robot can use its own actions and the corresponding action effects (i.e., visual observation of subsequent states) as ground truth labels for training its visual predictive model.
On the other hand, the robot can also use the statistics provided by the perception model (e.g., uncertainty, novelty, and predictability) as a reward signal to improve its manipulation policy. Ultimately, the robot could combine the learned visual predictive model and manipulation policy to facilitate efficient action planning for downstream tasks.
This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE). 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.
According to the current listing, eligibility includes: Early-career faculty at U. S. universities and colleges. Confirm the full requirements in the official notice before applying.
The current listing shows $600,000. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for CAREER: Active Scene Understanding By and For Robot Manipulation are due April 30, 2027. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
CAREER: Active Scene Understanding By and For Robot Manipulation is funded by National Science Foundation (NSF). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
MGPV Travel Grant is sponsored by Geological Society of America (GSA), Mineralogy, Geochemistry, Petrology, Volcanology Division. MGPV Travel grants support student travel to the annual GSA meeting. Applications are restricted to active graduate or undergraduate students who are the presenting authors of an accepted abstract at the annual GSA meeting.
Research Opportunities in Space and Earth Science (ROSES) - 2025: A.4 Rapid Response and Novel Research in Earth Science is sponsored by National Aeronautics and Space Administration (NASA) Science Mission Directorate (SMD). This omnibus research funding opportunity includes various program elements, with rolling submissions for Earth Science research through August 2026. Proposers to Earth Science using the NASA Center for Climate Simulation high-end computing facility must include specific budget details.
TCUP lists eight funding tracks and roughly $10.3M a year, but the October 14, 2026 deadline applies to only three of them — CHAI, Pre-TI, and TCUP Partnerships — and each carries a restriction that disqualifies most applicants. Here is the track-by-track math.
Read articleNSF 26-513 makes roughly $100 million available for up to 10 State and Regional AI Infrastructure Hubs at $4M to $12M each over five years. One award per state or multi-state region. One proposal per organization. And NSF is not buying you GPUs — it funds the coordination, the workforce and the faculty training, while the compute has to come from partners you have to already have.
Read articleAs of September 12, NSF had obligated $6.3 billion across 6,200 grants versus $8.1 billion and 8,600 last year. AHRQ has made 61 awards. Judge Allison Burroughs ordered the government to report by September 28 on whether IES will obligate $180 million before it expires. Here is what actually happens to the money on October 1 — and what it means for your FY2027 application.
Read article