Learning a Resolution-Consistent Jacobian Field for Bio-Inspired Rigid-Soft Finger
The Jacobian Flow Matching (JFM) framework learns a continuous Jacobian field that models how actuation transitions to motion dynamically. It addresses the challenge of making predictions accurate even when sensing and control resolutions vary, which is common in complex bio-inspired fingers. JFM improves prediction accuracy by over 53% compared to standard methods.