This Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will fund the development of advanced, vision-based tactile gel-robots capable of perceiving and manipulating soft, fragile objects. The $312,960 award will integrate fatigue-resistant photoelastic gels, stress-interpreting photometry systems, and physics-informed machine learning to enable multi-physical perception and ultra-gentle handling capabilities. This research will advance robotics in...
This Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will fund $489,214.00 in research at Oregon State University (OSU) from June 15, 2025 to May 31, 2028. The goal is to develop techniques to help robots recover from grasping failures in various settings, including homes and underwater environments. Key research focus areas include addressing grasping failures caused by unknown object parameters, unknown object dynamics, and unknown scene...
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 $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 Project Grant award of $330,133, provided by the National Science Foundation's (NSF) Engineering program (CFDA 47.041), supports research to advance robotic tactile sensing technology. The primary objectives are to develop innovative frameworks that enable robots to actively explore and perceive the physical properties of objects, such as hardness, texture, and slipperiness. This research aims to enhance robotic perception and manipulation capabilities, expanding the range of tasks robots...
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 $548,168 Project Grant award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program aims to develop and translate robotic manipulator technology for enhanced supply chain efficiency and dexterous material handling. The principal investigator's team at Columbia University will build on their previous work in deep reinforcement learning for complex robotic manipulation tasks, focusing on extrinsic manipulation strategies that can enable...
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...
The National Science Foundation awarded a $100,000 CAREER grant to Worcester Polytechnic Institute (WPI) under the Engineering program (CFDA 47.041) to conduct research on leveraging the collective power of robotic grasping algorithms through meta-learning and active perception. The project aims to develop ensemble learning methods and active vision strategies to improve the reliability of robots in manipulating objects in cluttered and unstructured settings. The research outcomes will be used...
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...