Adrian Hess

Sampling-Based Model Predictive Control for Dexterous Manipulation on a Biomimetic Tendon-Driven Hand

Biomimetic and compliant robotic hands offer the potential for human-like dexterity, but controlling them is challenging due to high dimensionality, complex contact inter-actions, and uncertainties in state estimation. Sampling-based model predictive control (MPC), using a physics simulator as the d