PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Strategy and Skill Learning for Physics-based Table Tennis Animation

Abstract: Recent advancements in physics-based character animation leverage deep learning to generate agile and natural motion, enabling characters to execute movements such as backflips, boxing, and tennis. However, reproducing the selection and use of diverse motor skills in dynamic environments to solve complex tasks, as humans do, still remains a challenge. We present a strategy [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

HaptiClay: An Interactive Haptic Interface for Gestured Concretization of Polynomial Functions

NSH 4305

Abstract: In this work we present HaptiClay, a low-cost kinesthetic haptic interface that elevates the understanding of mathematics language by providing embodied non-verbal representations of math concepts. Our interface integrates four key components: a haptic device, a high-level simulation that communicates with a low-level controller for force and position updates, a low-level controller that executes [...]