Project Grant 2220867
- This $272,290 three-year Project Grant from the National Science Foundation's Division of Computer and Network Systems will fund the development of visual tactile neural fields (VTNF) for active digital twin generation by robots. The grant supports research by The Trustees of the University of Pennsylvania under the NSF's $47.07 million Computer and Information Science and Engineering program. The researchers will create a new VTNF data representation that allows robots to combine visual and...
- The National Science Foundation awarded a $400,000 Project Grant to Stanford University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will fund a research collaboration titled "COLLABORATIVE RESEARCH: CPS: MEDIUM: CLOSING THE TELEOPERATION GAP: INTEGRATING SCENE AND NETWORK UNDERSTANDING FOR DEXTEROUS CONTROL OF REMOTE ROBOTS" from February 2021 through January 2024. The grant aims to advance investigator-initiated research and education in...
- 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...
- The National Science Foundation Division of Information and Intelligent Systems awarded a $750,000 Project Grant to Stanford University for research titled "COLLABORATIVE RESEARCH: NCS-FR: BEYOND THE VENTRAL STREAM: REVERSE ENGINEERING THE NEUROCOMPUTATIONAL BASIS OF PHYSICAL SCENE UNDERSTANDING IN THE PRIMATE BRAIN." The three-year grant, awarded October 1, 2021 and concluding September 30, 2024, will support research activities under the Computer and Information Science and...
- 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 $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...
- The National Science Foundation (NSF) awarded a Project Grant of $599,649 to Carnegie Mellon University (CMU) under the Computer and Information Science and Engineering (CFDA 47.070) program. The goal of this 3-year project, which commenced on April 15, 2024, is to develop perception systems that can infer the 3D structure of generic objects or scenes from 2D images, even with partial observations. Key technical efforts will include formulating mechanisms for learning novel 3D generative...
- This $466,714 project grant from the National Science Foundation's Engineering program (CFDA 47.041) supports the development of new expressive and differentiable robotics simulators at Stanford University from September 2022 through August 2026. The researchers will establish the mathematical foundations for simulators with learnable components, prototype such simulators, and evaluate their ability to reduce the "sim-to-real gap" where robots perform differently in simulation versus...
- This four-year, $400,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop new techniques for 3D scene understanding. Specifically, the Stanford University researchers will explore implicit neural representations to model scene structure and details from raw images and videos. They will integrate findings into course development and partner with organizations to teach artificial intelligence, computer vision, and...
- The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $600,000 Project Grant to the University of California, San Diego (UCSD) under the Computer and Information Science and Engineering (CFDA 47.070) program. The 3-year grant, effective July 1, 2023, supports research to develop dynamic neural network architectures that can efficiently enable multimodal perception, including vision, audio, and language processing. The research aims to address...
The National Science Foundation Division of Computer and Network Systems awarded a $337,020 project grant to Stanford University under the Computer and Information Science and Engineering program (CFDA 47.070) to support research on visual tactile neural fields for active digital twin generation. Over a three-year period from October 2022 through September 2025, Stanford researchers will develop new algorithms and computational tools to allow robots to combine visual and tactile sensory data into unified models of objects in their environment. The researchers will create mathematical techniques for robots to generate and improve visual tactile neural field models through physical interactions with objects. They will also develop methods to quantify model uncertainty and use this to inform efficient search policies for robots to generate accurate representations. The project aims to provide a flexible foundation for robotics researchers to enable faster learning through more detailed understanding of environments and interactions.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $337.0k | 8/31/22 |