This $349,000 National Science Foundation project grant supports research at Rice University to develop new robotics capabilities under uncertainty. The NSF Division of Civil, Mechanical, and Manufacturing Innovation is funding this three-year award through its Engineering program (CFDA 47.041). Specifically, the researchers will establish generic frameworks for robot manipulation systems to self-identify using exploratory motions while maintaining stability. By changing the traditional...
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 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 $499,076 National Science Foundation (NSF) grant awarded under the CFDA 47.041 Engineering program aims to develop efficient computational methods for robots to learn reliable dexterous manipulation skills without relying on significant human effort or computational resources. The principal objectives are to: 1) Learn dexterous manipulation skills from observations, 2) Learn multi-sensory representations and models from self-guided play, and 3) Analyze and guarantee learned manipulation...
This $50,000 Project Grant was awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) to The Leland Stanford Junior University (Stanford University) to develop a novel approach for robotic dexterous manipulation that leverages the powerful new object representation of neural radiance fields (NeRFs). The primary objective is to create an algorithmic pipeline that can go from camera pixels to grasp to manipulation trajectory, enabling complex manipulation skills such as...
This $150,000 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports fundamental research at the Rochester Institute of Technology (RIT) to develop new robotic manipulation capabilities for safely and reliably handling fragile objects. The research aims to establish an understanding of the synergy between vision and touch sensing, and to create a control method based on object properties that can optimize robotic manipulation for a variety...
This $349,032 project grant from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation Engineering Directorate supports research at Yale University to develop new paradigms for robot manipulation under uncertainty aided by passive adaptability. Specifically, the awardee will establish generic self-identification frameworks to allow robots to conduct exploratory motions that permit external perception of changes to generate online estimations and controllers....
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $290,000 to William Marsh Rice University (Rice University) to develop interpretable task and motion planning (TAMP) methods that can reason about uncertainty and incorporate implicit models. The 3-year project, beginning on May 1, 2024, aims to enhance TAMP with capabilities to handle noise in robot sensing and actuation, address pathological uncertainty, and integrate human preferences...
This four-year Project Grant from the National Science Foundation Division of Information and Intelligent Systems provides $599,998 to the University of Michigan for research titled "Overcoming Epistemic Uncertainty to Plan with Learned Dynamics Models for Robotic Manipulation." Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the award will support the development of techniques to help robots plan complex manipulation tasks despite uncertainty...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, supports a research project titled "CAREER: ACTIVE SCENE UNDERSTANDING BY AND FOR ROBOT MANIPULATION" at Stanford University. The $130,000 grant, awarded on October 1, 2023, aims to develop a self-improving robot perception system that leverages manipulation skills for active scene understanding. The key focus is on enabling robots to...
This National Science Foundation (NSF) Computer and Information Science and Engineering grant (CFDA 47.070) provides $50,000 to William Marsh Rice University to support research on enabling robust and dexterous robot manipulation capabilities for uncertain environments. The 5-year project, starting on June 1, 2023, explores a novel "manipulation funnels" framework to enable robots to handle uncertainties and unknowns through compliance- and motion-based strategies. This includes leveraging active or passive compliance to open initially blocked manipulation funnels, and using motion and task constraints to create funnels that reduce uncertainties. The research aims to enable complex manipulation tasks in highly uncertain scenarios that were previously infeasible. The grant will also support STEM education and outreach initiatives to broaden participation, including hands-on robotic tutorials and curriculum development.