Close-up of a robot gripper precisely picking a consumer product from a mixed-SKU bin

Solutions / Warehouse Picking

Pick-and-Place Operations
That Scale With Your SKU Catalog

Most warehouse robotic pick systems deliver consistent throughput on a stable, pre-programmed product set. The breakdown comes when SKUs change. Automcore decouples SKU onboarding from arm count — one training session, fleet-wide propagation, confidence-gated activation before production resumes.

The Challenge

Per-arm teach-in is the scaling ceiling for warehouse robotics

A robot arm in a DC is only as useful as its programmed SKU coverage. When SKU variety grows — seasonal product lines, new retail client onboarding, quarterly catalog rotations — the per-arm teach-in requirement becomes the operational bottleneck. Automcore removes that bottleneck at the model distribution layer.

Uniform Grasp Behavior Fleet-Wide

Every arm in your fleet runs the identical validated grasp model, distributed from a single training session. No arm-to-arm variation caused by inconsistent teach-in quality or different robot programmers. Gripper approach angle, grasp force, and pick sequence are uniform across the fleet for every trained SKU.

Training on One Arm; Fleet Picks Continuously

The training arm is taken offline for ~45 minutes per SKU during the capture session. All other arms in the fleet continue production picking throughout. Propagation to the full fleet runs during the next scheduled maintenance window — not during production shifts.

Per-Arm Pick Rate and Health Monitoring

Fleet Manager shows per-arm pick rates, SKU coverage counts, propagation status, and last-sync timestamps. Pick rate drops that deviate more than 15% from the arm's 7-day average generate an alert, prompting the operations team to investigate before the issue affects pallet output targets.

Confidence-Gated Activation — No Silent Failures

Each arm runs a local grasp confidence simulation after receiving a propagated model. Arms that pass the configured threshold (typically 92–95%) activate for production. Arms below threshold are flagged in Fleet Manager and held for a follow-up session. A dropped pallet from a low-confidence grasp is worse than a delayed propagation — we treat them that way.

Performance Data

Benchmark numbers from live deployments

Per-arm pick rate — mixed SKU

380–640 picks/arm/hr

Mixed-SKU depalletizing across 12-arm fleets. Upper bound for rigid consumer goods with vacuum cup; lower bound for flexible packaging requiring force-torque calibration.

First-session validation pass rate

97.4%

Percentage of arms that receive and validate a propagated model without requiring a follow-up session.

SKU introduction time

~45 min

Single training session on one arm to capture a new SKU — regardless of fleet size.

Fleet propagation window

<8 hrs

End-to-end propagation to a 12-arm fleet over facility gigabit LAN during a maintenance window.

Talk to us about your warehouse picking operation.

We'll assess your fleet configuration, SKU volume, and changeover frequency to scope an Automcore deployment.