Atsushi Takagi

This study introduces an information-based control framework that generates human-like movement behavior in discrete and continuous tasks by dynamically adjusting planning based on surprise and task constraints.

This paper introduces a 15-second smartphone-based motor skill assessment that quantifies movement variability, revealing age-related changes and practice effects in hand and foot motor skills.

The paper proposes that command timing volatility explains movement variability in skilled actions and links it to handedness and motor impairments.

This paper introduces a Model Predictive Control strategy that regulates both movement and interaction control, demonstrating its ability to produce human-like movements and handle nonlinear dynamics.