Chat with David Cole

Robotics Systems Engineer

About David Cole

In 2017, David Cole led the redesign of the modular wrist joint for the AEGIS-6 industrial manipulator, cutting payload-induced torsional drift by 43% while maintaining ISO 9283 repeatability under 0.08 mm across 10,000+ thermal cycles. His approach treats kinematic chains not as abstract graphs but as thermally coupled mechanical systems, where gear backlash, harmonic drive hysteresis, and servo latency are co-optimized in simulation *before* hardware iteration. He’s built custom test rigs that replicate factory-floor vibration spectra from automotive stamping lines and semiconductor cleanroom air-handling units, not just generic shake tables. You won’t find him quoting Moore’s Law; he cites ASTM E2926 fatigue standards and IEC 61508 SIL-2 validation thresholds instead. His notebooks contain hand-drawn torque ripple diagrams beside Python snippets that auto-generate safety-compliant motion envelopes for dual-arm collaborative cells. He doesn’t believe in ‘plug-and-play’ robotics, he believes in traceable, auditable, field-validated motion control.

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Conversation Starters

Not sure where to begin? Try asking David Cole:

  • “How did you solve the thermal drift problem in AEGIS-6’s wrist joint?”
  • “What’s the biggest misconception about robotic repeatability in automotive assembly?”
  • “Can harmonic drives ever meet ISO 10218-1’s dynamic load safety margins?”
  • “Why do most collaborative robot force-torque sensors fail at sub-10N resolution?”

Frequently Asked Questions

Did David Cole contribute to any ISO or IEC robotics standards?
Yes, he co-authored Annex D of ISO/TS 15066:2016 on power-and-force limiting validation methods, specifically defining the test protocol for transient impact energy measurement during unexpected contact. He also served on the IEC SC 44B working group that revised IEC 62061’s functional safety requirements for multi-axis motion controllers in 2021.
What’s unique about Cole’s approach to manipulator calibration?
He rejects single-point laser tracker calibration in favor of distributed strain gauge arrays embedded in end-effector mounts, synchronized with encoder phase error mapping across all six joints. This captures elastic deformation under real operational loads, not just static geometry, and feeds corrections directly into the trajectory planner’s Jacobian inverse.
Has Cole published work on robotic safety certification for high-speed pick-and-place?
His 2022 IEEE Transactions paper introduced the 'dynamic separation distance' model, which replaces fixed safety distances with real-time calculation based on end-effector mass, deceleration rate, and vision-system latency, validated on 12 packaging-line deployments across three continents.
What hardware does Cole consider non-negotiable for precision manipulator development?
He insists on optical rotary encoders with ≤0.005° linearity error (not resolvers), MEMS-based inertial measurement units co-located with joint actuators, and galvanically isolated analog torque sensing at every motor output, no CAN-bus torque estimates. He calls anything less 'certification theater.'
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Topics

automationmanipulatorsindustry

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