Project Grant 2319471
- The National Science Foundation awarded a $800,000 Project Grant to the University of Texas at Austin under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support the development of a neurosymbolic program-synthesis framework that closely couples deep learning and classical symbolic methods for program synthesis. Researchers will explore new learning algorithms exposing neural models of code to explicit knowledge about program semantics....
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $399,158 to the University of Texas at Dallas (UTD) to develop a new learning framework that enables robots to understand and imitate object-based manipulation tasks. The project will design models to allow robots to recognize and segment objects from visual memory, learn how to grasp objects by observing human contact patterns, generate...
- This $375,000 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The goal of the project is to develop tools and methods to help ensure the safe operation of autonomous systems that utilize reinforcement learning (RL) algorithms. Key activities include: 1) developing inverse RL algorithms to learn an agent's reward function from demonstrations, 2) exploring the agent's norms to...
- This $899,109.00 project grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to advance the state of the art at the intersection of robotics, artificial intelligence, and formal verification. The research seeks to develop new algorithms for the synthesis and verification of interpretable robot control programs that enable transparent, trustworthy, and reliable robot learning in real-world settings....
- This National Science Foundation Project Grant award of $549,995 supports research and education activities at the University of Texas at Austin from April 1, 2022 through March 31, 2027. The award is funded through the Computer and Information Science and Engineering program (CFDA 47.070) to enable intelligent robot manipulation in real-world tasks. Specifically, the award will advance the development of new algorithms and tools for intelligent robot manipulation outside controlled research...
- This Project Grant award for $50,000.00, provided by the National Science Foundation (NSF) Engineering program (CFDA 47.041), aims to develop a framework for learning complex, long-horizon tasks from few-shot vision-language demonstrations. The primary objective is to enable robots to learn personalized tasks through natural interactions with users, who can provide visual demonstrations combined with language narration. The research leverages large language models to summarize vision-language...
- This $439,425 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research to enable the safe deployment of learning-enabled systems that can robustly learn and optimize their behavior based on uncertain human feedback and intent. The key objectives are to: (1) develop methods for providing probabilistic performance guarantees when learning policies from human input,...
- The National Science Foundation Division of Information and Intelligent Systems awarded a $545,980 Project Grant to Princeton University from August 1, 2021 through July 31, 2026 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant funds research at Princeton University to develop generalization and safety guarantees for learning-based control of robots. The Computer and Information Science and Engineering program supports investigator-initiated research...
- The National Science Foundation awarded a $590,469 project grant to the University of Texas at Austin on April 1, 2021 for research titled "CAREER: ROBUST PERCEPTION AND CUSTOMIZATION FOR LONG-TERM AUTONOMOUS MOBILE SERVICE ROBOTS." The grant is funded through the NSF's Engineering program (CFDA 47.041), which seeks to improve quality of life and economic strength through engineering research and education. Under this five-year project grant, the University of Texas at Austin will...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program Project Grant, awarded to Georgia Tech Research Corporation, will develop a new robotic learning system that enables rapid adaptation and continuous skill acquisition for service robots. The $574,930 award, with a performance period from July 1, 2025 to June 30, 2030, will fund research on coupling intelligent planning and learning to allow robots to learn new skills from human teachers and...
This $750,000 Project Grant was awarded by the National Science Foundation (NSF) Division of Computing and Communication Foundations under the CFDA program "Computer and Information Science and Engineering." The grant was awarded to the University of Texas at Austin to develop a new paradigm for robot learning from demonstrations (LfD) using program synthesis techniques. The research aims to address limitations in existing neural network-based LfD approaches by combining them with symbolic reasoning to create interpretable, verifiable, and data-efficient programmatic policies for robots. Key project objectives include 1) introducing a language to merge neural and symbolic program components, 2) providing guarantees on program correctness, and 3) enabling LfD from noisy, real-world data. This work is expected to advance the state-of-the-art in robot learning, program synthesis, and verified learning. No subawards are planned under this grant, which runs from October 2023 through September 2027.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $750.0k | 8/30/23 |