Vincenzo Ceccarelli GrimaldiCluster · Physical AI
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palletizer CORE

Robot-agnostic palletizing software: mixed-SKU pallet planning with a checkable stability number, deterministic orchestrator, hardware-agnostic robot and gripper interfaces, telemetry, MCP tool server, native C++ packer, ROS 2 bridge, browser optimizer.

github.com/iceccarelli/palletizerpypi · palletizer-full-stack 0.2.0palletizer-app.vercel.app (stated, not verified here)

Repository
github.com/iceccarelli/palletizer
Cluster
physical-ai
Status
CORE
Language
Python, TypeScript, C++
Activity
last commit (live, as of 2026-09-05) · 0 stars · 0 open issues
Architecture
Six Python packages (core, control, perception, planning, power, orchestrator) around a fixed-rate deterministic loop; optimizer with pybind11 accelerator; Next.js 14 web app; MCP stdio server; ROS 2 integration package.
Dependencies
Python ≥ 3.11 · pybind11 / CMake (optional) · Next.js 14 · ROS 2 (optional, lazy)
Maturity
alpha
Business hypothesis
A customer can deploy a palletizing cell faster and run it cheaper than with the incumbent integrator-built control software, because planning, stability checks, safety logic and telemetry are not rewritten per cell.
Customer
None contracted. Targets: system integrators, packaging companies, 3PL warehouses.
Technical role
First commercial candidate. Owns task planning, pallet optimisation, orchestration, telemetry.
Duplicate functionality
construction/ vertical pack overlaps the Operations cluster (FloorForge, DryForge) and is under kill-rule review.
Strategic value
high
IP value
medium
Revenue potential
medium
Integration potential
high
Security risk
medium
Regulatory implications
ISO 10218 / ISO/TS 15066 apply to any cell that executes; the software makes no certification claim.
Recommended status
COREThe only repository in the cluster with a public package, a test suite and a runnable optimizer. It is CORE because everything else in the cluster is measured against whether it makes this cheaper to deploy.

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