Sensing Architecture

PaXini PX-6AX GEN3 is built around dense, spatially distributed tactile sensing rather than single-point force detection. The system exposes local contact geometry, directional force information, and temporal changes across the sensing surface so downstream models can reason about slip, shear, incipient contact, and force redistribution.

Output Semantics

The expected output is not just a scalar force number. Each frame is a structured tactile observation made of per-cell triaxial force values plus an aggregated contact state. This makes it easier to fuse touch with vision, joint states, and policy metadata during learning or evaluation.

Calibration Workflow

Before using the sensor in dataset collection, validate baseline noise, ensure stable mechanical mounting, verify contact repeatability under known loading, and check how the sensor behaves during repeated low-force interactions. Calibration is about preserving consistency across sessions so policy training data remains trustworthy.

Mechanical Integration

Mount the sensor so contact events are mechanically meaningful relative to the task. Control how the sensing layer is exposed, how the end-effector distributes pressure, and how cable routing or protective covers affect deformation behavior. Mechanical integration has a direct effect on data quality, not just packaging.

Software Integration

In most learning workflows, timestamp and log the tactile stream together with joint states, actions, camera frames, and task metadata. Consistent observation packaging makes it easier to train multimodal policies, replay failures, or compare operator demonstrations across hardware iterations.

Best practice — Treat tactile signals as part of the full robot observation schema, not an auxiliary debug channel.

Deployment Checklist

  • Verify stable mounting and cable routing before contact testing.
  • Record a clean no-contact baseline for reference.
  • Check repeatability under repeated low-force contacts.
  • Log tactile frames with synchronized task and robot state metadata.
  • Validate failure cases such as partial contact, shear, and slip.

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