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Applied PDE Group
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human-robot interactions

Model Predictive Control and Imitation Learning Algorithms for Robot Motion Planning in Physical Human-Robot Interaction

Aigerim Nurbayeva, Postdoctoral Research Fellow, Electrical and Computer Engineering
Mar 15, 12:00 - 13:00

B9 R2325

Model Predictive Control robotics deep neural networks Numerical Optimization universal robot human-robot interactions NMPC

This seminar presents a framework for safe and efficient human-robot workspace sharing by using Deep Neural Networks (DNN) and safety filters to rapidly imitate computationally heavy Nonlinear Model Predictive Control method (NMPC), with successful experimental validation on a UR5 manipulator.

Core Challenges in Navigation in Human Environments

Jean Oh, Senior Systems Scientist, Robotics Institute, Carnegie Mellon University

Mar 31, 16:30 - 17:15

KAUST

Featured Sessions

RobotoKAUST Social robot navigation motion planning motion prediction human-robot interactions

For more information please visit the website

Safe, Interaction-Aware Decision Making and Control for Robot Autonomy

Marco Pavone, Associate Professor, Aeronautics and Astronautics, Stanford University

Apr 1, 21:15 - 22:15

KAUST

Featured Sessions

RobotoKAUST human-robot interactions decision making autonomous driving

For more information please visit the website

Applied PDE Group (AppliedPDE)

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