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University of Penn- sylvania
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AD-MPCC achieves faster lap times and enhanced safety in autonomous racing by dynamically adapting to road conditions in real time.
Effective AI coaching can accelerate human skill development by strategically balancing assistance and independence, leading to superior learning outcomes in motor tasks.
Achieve safer and more performant robot control in iterative tasks by using normalizing flows to learn value functions within a model predictive control framework.
Autonomous vehicles can now nimbly navigate complex 3D terrain thanks to a novel MPC framework that learns and adapts to nonplanar geometry in real-time.
