NSF award 2556205 · University of Maryland, College Park

Collaborative Research: RI: Gaussian Processes that Embrace Heterogeneity for Multi-Sensor Sampling Mission

Final report due

29 December 2029

in 1,168 days · The award ends on 31 August 2029.

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Decide about an extension3 May 2029in 928 days
award ending 2029-08-31 · Research.gov
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Extension request17 Jul 2029in 1003 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2029in 1038 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2029in 1168 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2029in 1168 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2029in 1168 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 31 August 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 December 2029.

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Award card

Award number: 2556205
Period of support: 1 Sep 2026 – 31 Aug 2029
Amount: $666,666
Awardee: University of Maryland, College Park, College Park, MD
Program: Robust Intelligence
Directorate: CSE

Abstract

Scientists, engineers, and decision makers rely on maps built from sensor data to understand the world, predict its properties, and make informed decisions. Creating accurate maps can be difficult, time consuming, and expensive because collecting data samples often requires visiting specific physical locations to take sensor measurements or gather specimens. This project studies how autonomous systems can gather…

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