This Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will support research to enable rapid and continuous adaptation of service robots. The $323,874 award to the Georgia Tech Research Corporation will develop a new robot learning system that combines intelligent planning and occasional human guidance to help robots quickly learn new skills and adapt to new tasks. The goal is to create home robots that...
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 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 $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 $349,000 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 $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 $140,000 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to revolutionize teleoperation technology for dexterous in-hand manipulation in human-robot collaboration. The primary research objectives are to: 1) develop a learning-based robot control policy to interpret human commands using end-effect-based task features, 2) create a safety-aware, multi-modal perception system to optimize sensory inputs for intuitive and safe operation, and...
This $454,020 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) will support collaborative research at the University of Michigan to develop soft materials with embedded sensors, circuits, and actuators enabling a new class of intelligent soft robots. The goal is to create a soft robotic manipulator that can autonomously recognize and sort objects by their physical characteristics using only these advanced material components, without requiring...
This $272,617 National Science Foundation (NSF) Engineering program (CFDA 47.041) award to the University of Illinois supports fundamental research on high-dimensional proprioceptive and tactile sensing methods for soft robotic grippers. The project aims to develop a new framework, called DeepSORO, that uses embedded cameras and advanced deep learning models to provide real-time, high-resolution sensing and state estimation of the grippers' kinematics and dynamics. This research seeks to...
The National Science Foundation awarded a $438,863 Project Grant to the Regents of the University of Minnesota under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The five-year award will support the development of novel computational algorithms to enable robots to visually understand scenes, learn manipulation action sequences, and adapt to different environmental settings for challenging object grasping. Specifically, the Principal Investigator...
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 skills. This 5-year project, awarded to the Georgia Tech Research Corporation, will deliver insights and open-source technologies with broad relevance to robotics problems involving high-dimensional systems and nonlinear dynamics. The grant includes a multi-faceted education and outreach program to engage high school students from marginalized groups in rapidly-growing areas of science and research careers.