T2UD-MISManufacturingAutomotive
Robotic path planning / motion deconfliction
Deconflict robot motions in a shared cell — time-expanded conflict graph; near-native if kept 2D.
Sector
Manufacturing / robotics
Likely buyer
Automation integrators; automotive lines
Hardware gate
Orion; time-expansion grows the graph
Taxonomy
throughput-limited × accelerating
Live demo — adiabatic sweep on 5 motions
Ω 9.4 · δ ±12.6 rad/µs · 4000 ns · R_b 9.1 µmRobot motions conflict when their space-time envelopes overlap; maximize simultaneous safe motions.
GTM talk track
'Colliding robot paths are conflicts in space-time — deconflict the most motions at once.'
OGSM — product operating frame
Objective
Demonstrate motion deconfliction in a cell.
Goals
- One integrator runs a cell
Strategies
- Keep the conflict graph 2D
Measures
- Motions scheduled
- Cycle time
OBR — outcome-based roadmap
| Horizon | Outcome we create | Buyer behavior change | Result we measure |
|---|---|---|---|
| Now | Integrator sees deconfliction in a cell | Prospect runs the emulated demo on their own instance data | Booked QPU-time evaluation or paid pilot |
| Next | Integrator benchmarks a line | Prospect co-designs a scoped benchmark against their incumbent solver | Documented crossover curve; expansion to production instances |
| Later | Integrator adopts | Prospect standardizes on the workflow or buys an on-prem system | Recurring QPU consumption / system sale; reference case |
Fit notes (honesty gate)
Time-expanded conflicts; near-native if kept 2D.
Ready to run this on real hardware?
Emulation-verified today — the same program runs on a Pasqal QPU unchanged.