2026 / Research

P-V Fatigue Manifold Proprioception

Simulation study of pressure-volume loop shape as a candidate recalibration signal for pressure-only soft-gripper proprioception.

Result: P-V loop area tracks compliance drift at r = 0.885 on held-out actuators; the deployed threshold has no positive temporal lead.

This research asks whether a signal already present in pneumatic control—the pressure-volume hysteresis loop—can track fatigue-driven drift and trigger pressure-only proprioception recalibration in a shared-manifold soft gripper. The result is a transparent simulation pipeline, frozen evaluation, and v1.3 manuscript.

Category
Research
Timeline
Jun. 2026 - Jul. 2026
Status
Complete
Tools
Python / NumPy / SciPy / Matplotlib

Problem

What the build needed to solve

My contribution

Built the generative model, actuator-identity split, health-indicator and recalibration evaluation, audit checks, figures, and manuscript/release package.

Soft pneumatic grippers age, while pressure-only pose estimators drift with compliance. A useful health indicator must generalize across actuators and must be audited against a simple clock baseline and an explicit temporal-lead definition.

Constraints

Design boundaries

Split train and test data by actuator identity rather than by trace.

Keep every claim simulation-only until matched hardware evidence exists.

Report negative or threshold-dependent findings without moving the selection rule.

Make manuscript numbers machine-checkable against committed JSON results.

Build log

Design evolution

Iterations, issues, and fixes documented as a compact notebook timeline.

Mechanism model

A plausible shared-manifold effect could be asserted without separating it from global fatigue drift.

Built isolated-versus-shared supply simulations and actuator-level held-out splits.

Cross-talk exists but is second-order at the registered parameters.

Lead-time audit

The selected trigger met the error budget but did not provide warning before violation.

Reported a threshold frontier instead of relabeling the deployed threshold.

Median lead is -0.123 normalized life at the deployed threshold; lower thresholds can buy lead at a recalibration cost.

Citable package

arXiv endorsement is an external dependency.

Frozen v1.3 bytes, citation metadata, and an August 2 Zenodo fallback.

The application packet no longer depends on an inbox response.

Held-out P-V health indicator and threshold lead-time analysis
Held-out health-indicator relationship and threshold-dependent lead-time result

Testing

Results

Dataset

2,000 traces

Held-out correlation

r = 0.885

95% CI

0.835–0.958

Trigger recalibrations

2 vs 5

Deployed median lead

-0.123 life

Evidence

Simulation-only

The full suite validates the pneumatic plant, fatigue model, health features, shared-manifold network, actuator-level evaluation, and manuscript-number traceability.

The strongest evidence is not a perfect positive result: the registered trigger saves recalibrations but provides no positive warning time at the deployed threshold.

Scope note: All actuators are generated by one simulation family. No physical fatigue, P-V, or proprioception validation is claimed.

Reflection

Engineering lessons

  • A health indicator and a leading indicator are different claims.
  • Actuator-identity splits are essential when traces from one specimen are correlated.
  • A simple cycle-count baseline can expose whether sensing adds operational value.

Links

Files and references