FRR: Learning Object-Centric Representations from Human Demonstrations for Robot Manipulat — NSF Award to University of Texas at D
Most robots today work in factories where people need to program every step of a task. This project explores how to make robots easier to use by helping them learn from watching people. This project uses artificial intelligence using reinforcement and imitation learning approaches. The goal is to teach robots how to se
| Award title | FRR: Learning Object-Centric Representations from Human Demonstrations for Robot Manipulat |
|---|---|
| Award ID | 2520553 |
| Awardee | University of Texas at Dallas |
| City | RICHARDSON |
| State | TX |
| Amount obligated | $399,158 |
| Principal investigator | Yu Xiang |
| Program | FRR-Foundationl Rsrch Robotics |
| Start date | 09/01/2025 |
| Abstract | Most robots today work in factories where people need to program every step of a task. This project explores how to make robots easier to use by helping them learn from watching people. This project uses artificial intelligence using reinforcement and imitation learning approaches. The goal is to teach robots how to see and handle objects by using video demonstrations of humans performing different actions. This is especially helpful with learning to grasp and move objects that have never been s |
| Source | NSF Awards |
$799/mo
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