Project Grant N000142312845

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 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program ($199,481) supports research at George Mason University from June 2023 through May 2026 to develop an approach for improving service robot decision-making and behavior during deployment in unfamiliar environments. The award aims to facilitate fast and reliable online retraining and adaptation of robot planning despite missing world knowledge. The researchers will develop a...

This NSF CISE program Project Grant award of $544,114 to New York University (NYU) is funding research on "NUMERICALLY EFFICIENT REINFORCEMENT LEARNING FOR CONSTRAINED SYSTEMS WITH SUPER-LINEAR CONVERGENCE (NERL)". The project aims to develop new reinforcement learning algorithms that can more efficiently create behaviors for real-world robotic applications, while ensuring operational safety. The research will explore ways to improve learning efficacy and guarantee safety, and will...

This five-year, $548,928 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support research into developing robots that can learn about their environments through natural spoken language interactions with diverse groups of people. The principal investigator at the University of Maryland Baltimore County will study how robots can acquire an understanding of...

This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) program provides funding of $1,186,632 to The Leland Stanford Junior University (Stanford University) for a research project titled "NRI: HIERARCHICAL REPRESENTATION LEARNING FOR ROBOT ASSISTANTS." The project aims to develop an automated robot assistant that can recognize a person's goals and provide the right objects at the right time, enabling people with...

This five-year, $205,073 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support research at Tufts University to develop methods for transferring multisensory object knowledge across collaborative robots. The Principal Investigator will work to enable robots with different bodies, sensors and movement capabilities to learn from each other's experiences manipulating and perceiving objects through various senses. This...

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...

This three-year, $500,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop strategies for robotic manipulation without prior shape models of objects. The Massachusetts Institute of Technology will receive funding to design a state-estimation and task planning system that combines neural network perception with uncertainty modeling. This will enable robots to operate in less restrictive, real-world environments like...

This three-year, $500,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund research at the University of California, Davis to develop trustworthy machine learning systems through adversarial robust reinforcement learning. Specifically, the award supports investigating potential vulnerabilities in reinforcement learning models and algorithms, developing robust RL approaches that mitigate impacts from adversarial attacks, and...

This Project Grant from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) awarded $400,000 to Carnegie Mellon University for the collaborative research project "Aligning Robot Representations with Humans". The project aims to enable robots to learn representations that are aligned with human preferences and values, through the development of new types of human feedback and algorithms to efficiently learn from them. The key objectives are...