Physical AI & Robotics · cluster control engine
Prove whether physical autonomy can create a defensible second moat.
One place that states what this cluster owns, what it measures, what it has decided and what it has killed — as pages and as JSON. Robot-agnostic palletizing software first; everything else is judged by whether it makes that cheaper to deploy.
Mission
- PERCEIVE
- MODEL
- PLAN
- ACT
- VERIFY
- RECOVER
- LEARN
| Entry | PERCEIVE | MODEL | PLAN | ACT | VERIFY | RECOVER | LEARN |
|---|---|---|---|---|---|---|---|
| palletizer | · | ■ | ■ | · | ■ | · | · |
| robot-lidar-fusion | ■ | · | · | · | · | · | · |
| palletizer-mcp | · | · | ■ | · | · | · | · |
| palletizer-native | · | · | ■ | · | · | · | · |
| entries per stage | 1 | 1 | 3 | 0 | 1 | 0 | 0 |
Do not build robots because robots are exciting. Find a repetitive physical task where:
- labour is expensive
- task frequency is high
- the environment is sufficiently structured
- failure cost is understood
- automation can be measured
- the customer already has budget
- deployment is technically feasible
Status board as of
Repository register
Six statuses, no seventh. Every row names a public artifact or says none. Last-commit dates are live from GitHub when reachable, otherwise the dated snapshot.
| Repository | Status | Public artifact | Last commit |
|---|---|---|---|
palletizergithub.com/iceccarelli/palletizer | CORE | github.com/iceccarelli/palletizer +2 | snapshot |
robot-lidar-fusionrobot-lidar-fusion (repository path not public) | CORE | pypi · robot-lidar-fusion 0.4.0 | not public |
palletizer-simulationpalletizer/core/simulation · palletizer/web (R3F + Rapier) | MODULE | palletizer/core/simulation | snapshot |
palletizer-ros2palletizer/ros2_integration | MODULE | palletizer/ros2_integration | snapshot |
palletizer-mcppalletizer/mcp | MODULE | palletizer/mcp | snapshot |
palletizer-nativepalletizer/native | MODULE | palletizer/native | snapshot |
palletizer-constructionpalletizer/construction | EXPERIMENT | palletizer/construction | snapshot |
autonomous-inspectionautonomous inspection / HV inspection robotics (no repository located) | RESEARCH | none | not public |
ai-agent-controlgithub.com/iceccarelli/ai-agent-control | EXPERIMENT | github.com/iceccarelli/ai-agent-control | snapshot |
First target — palletizing
Twelve KPIs the mandate names. A dash means unmeasured; a target is never printed as a result. The simulator has to produce these before any hardware is touched.
- Cycles / hour unmeasuredcycles/h
- Successful picks unmeasuredcount
- Failed picks unmeasuredcount
- Intervention rate unmeasuredper 1,000 cycles
- Changeover time unmeasuredmin
- Deployment time unmeasureddays
- Robot utilisation unmeasured%
- Gripper utilisation unmeasured%
- SKU complexity unmeasuredSKUs/order
- Downtime unmeasuredmin/shift
- Labour savings unmeasuredh/shift
- Payback period unmeasuredmonths
Safety gate
Probabilistic intelligence proposes; deterministic safety refuses. No model, learned or language, reaches an actuator except through this gate, and no tool exists that bypasses it.
- PLAN
- SIMULATE
- VALIDATE
- AUTHORIZE
- EXECUTE
- VERIFY
Agents may
generate_plananalyze_scenepropose_actionretrieve_procedurediagnose_failureoptimize_schedulegenerate_simulation_scenario
Agents may not
command_actuatormodify_safety_limitmodify_production_behaviorbypass_gate
Latest decisions
Weekly CEO report 2026-W36
Next experiment
Palletizer KPI harness: a headless simulation run over a published fixture set that writes cycles/hour, successful/failed picks, intervention proxies and changeover time to a versioned JSON file. Success = the file exists, is reproducible from a clean clone, and /palletizer reads it.
Decision required
Three: (a) freeze or keep palletizer/construction; (b) publish the robot-lidar-fusion repository or accept that it stays package-only; (c) approve the discovery target of ten buyer conversations by 2026-09-19.
Not in this cluster
Applications that look physical and are not robotics products. They stay where they are until a robot executes a physical task under the gate.
- FloorForge AI INTERNAL operations — Stays in Operations until there is actual physical robotic execution. Concept renders are not robots.
- PaintForge AI INTERNAL operations — Stays in Operations until there is actual physical robotic execution.
- DryForge AI INTERNAL operations — Stays in Operations until there is actual physical robotic execution.
- GridOS · DERIM · energie-teilen INTERNAL energy — Energy Intelligence. Physical AI talks to them through versioned events only (see /contracts).
- No customer = no scale.
- No benchmark = no performance claim.
- No ROI = no product.
- No safety = no deployment.
Operator
Vincenzo Ceccarelli Grimaldi
Frankfurt am Main
ITk Fachspezialist, DB InfraGO AG. Traction HV digitisation. IT/OT. KRITIS-class governance.
Grid and traction-power work — the CIM–ThreMA thesis simulator and the public-dataset application — stays under Work and Thesis. /work · /simulator
Enquiry
System integrators, packaging companies, warehouses, inspection companies, utilities: one sentence about the task that costs you the most labour is enough to start. Replies come from the address in the footer.