EAGER: TaskDCL: Mutual Learning and Adaptation for Human-Robot Sensorimotor Interactions i — NSF Award to Arizona State University
This EArly-concept Grant for Exploratory Research (EAGER) project will support research that intends to create a new modeling and learning framework to enable a human and robot to coordinate efficiently through sensorimotor interactions in urgent and safety-critical tasks. Human-robot sensorimotor interactions have shi
| Award title | EAGER: TaskDCL: Mutual Learning and Adaptation for Human-Robot Sensorimotor Interactions i |
|---|---|
| Award ID | 2431479 |
| Awardee | Arizona State University |
| City | SCOTTSDALE |
| State | AZ |
| Amount obligated | $300,000 |
| Principal investigator | Wenlong Zhang |
| Program | Dynamics, Control and System D, M3X - Mind, Machine, and Motor |
| Start date | 09/01/2024 |
| Abstract | This EArly-concept Grant for Exploratory Research (EAGER) project will support research that intends to create a new modeling and learning framework to enable a human and robot to coordinate efficiently through sensorimotor interactions in urgent and safety-critical tasks. Human-robot sensorimotor interactions have shifted the paradigm in manufacturing, transportation, and healthcare over the past decade. However, most existing robots can only function in human-led, highly repetitive, and slow t |
| Source | NSF Awards |
$799/mo
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