Edge control plane · exclusive package
Skill state that fits on the robot
Sparse multi-step soft-state over large named skill inventories when only a few are live — CPU-side, beside the stacks you already trust.
connecting…
Embodied platforms carry thousands of named skills and modes. Dense multi-step soft-state blows RAM and milliseconds when only a few are live. Drop to non-evolving heuristics and you lose the path-dependent register the body needs on a new site.
cues (zones · failures · HRI · battery)
│
▼
┌─────────────────────────────┐
│ OSH-Sense control plane │ CPU / MCU-class
│ skill / mode register │ k ≪ N live
│ online φ · Hybrid gate │
└──────────────┬──────────────┘
│ instruction
▼
your motion · grasp · nav ← frozen stacks you already own
Not a perception net. Not a locomotion policy. Not a cloud agent product.
Join the queue. This server’s CPU runs a MuJoCo Humanoid Sense skill bank (N=4096 — above the dense crossover) and streams intents — primary skill, live support k ≪ N, emergent probes — while hardware meters prove progress on this class of box.
Sparse inventory crystallizing — not a gait showcase in five minutes.
Low N: dense can win. High N: dense climbs; OSH stays near-flat — the tool to scale soft-state on the edge.
Measured · realtime + context-scale · log-y
Measured · footprint bench · log-y
IP + team. NDA evidence pack if you need to verify first. Leave a note — or email directly.