ATLAS
Five Robots, One Brain
Five warehouse robots sharing one collective intelligence. When Robot A maps a new aisle, ALL robots know in 2 seconds. No central server. No single point of failure. The fleet gets smarter per-unit as it grows.
THROUGHPUT AT 50 ROBOTS
42×
TIER 3 // 07
ROBOT FLEETS ARE ISLANDS
Each robot maps independently — building its own private world model from scratch. Central planners like Symbotic create brittle single-server architectures. Coordination overhead alone kills throughput: 50 robots should deliver 50× output, but you get 30× at best.
- 50
- ROBOTS, EACH ALONE
- 1
- SERVER = BOTTLENECK
- 30×
- ACTUAL THROUGHPUT (NOT 50×)
DECENTRALIZED SHARED INTELLIGENCE.
ATLAS chains nine research models into a fleet-wide operating system. Four modules run fleet-wide — building and sharing a collective 3D semantic map in real time. Five modules run per-robot — giving each unit full perception and manipulation autonomy. No central server. Every robot is both client and node.
MODULE CHAIN:Fleet: SYNTHESIS → NEXUS → LOCI → HERMES // Per-robot: AZOTH → MONAD → PROTEUS → ERGON → CHIRON
- 01fleet
SYNTHESIS
Shared 3D Gaussian Map
Fleet-wide 3D Gaussian splatting map that merges observations from every robot in real time. One robot scans, all robots see.
- 02fleet
NEXUS
Semantic Zone Mapping
Carves the shared map into semantic zones — pick stations, staging areas, hazard corridors. Robots reason about places, not coordinates.
- 03fleet
LOCI
Cross-Robot Place Recognition
90.48% accuracy cross-robot place recognition. Robot C recognizes a location Robot A mapped hours ago — no GPS, no fiducials.
- 04fleet
HERMES
Fleet-Aware Navigation
Decentralized path planning that uses the shared map. Robots negotiate corridors, avoid deadlocks, and dynamically reroute without a central planner.
- 05robot
AZOTH
Object Detection
Real-time detection of packages, pallets, obstacles, and humans. Each robot sees its local world with sub-50ms latency.
- 06robot
MONAD
Persistent Tracking
Tracks every detected object across frames with persistent IDs. A pallet picked up by Robot B stays tracked when Robot D takes over.
- 07robot
PROTEUS
Instance Segmentation
Pixel-precise segmentation of every object in view. Separates overlapping items on cluttered shelves for reliable grasp planning.
- 08robot
ERGON
6DoF Pose Estimation
Full 6-degree-of-freedom pose for every detected object. Millimeter-accurate orientation data for robotic manipulation.
- 09robot
CHIRON
Force Control
Adaptive force feedback for grasping and placement. Handles fragile items and irregular shapes without crushing or dropping.
FOR LOGISTICS
ATLAS turns isolated robots into a collective organism. The shared semantic map IS the product — it compounds with every robot added. Warehouses stop scaling linearly and start scaling exponentially.
- 01Fully decentralized — no single point of failure. Kill any robot, the fleet keeps working.
- 02Sublinear cost scaling — each additional robot costs less to integrate because the shared map already exists.
- 03Data flywheel — every meter every robot travels enriches the collective map. More robots = smarter per-unit intelligence.
KEY NUMBERS
- 42×
- THROUGHPUT AT 50 ROBOTS
- 2-3SEC
- FLEET MAP SYNC
- $35K/ROBOT
- UNIT COST AT 50
- $25B
- ADDRESSABLE MARKET
WHERE THE VALUE IS
| 3PL WAREHOUSE AUTOMATION | $10B |
|---|---|
| COLD-CHAIN LOGISTICS | $5B |
| MANUFACTURING INTRALOGISTICS | $5B |
| PORT AUTOMATION | $5B |
THE MOAT
Most logistics robots are islands. ATLAS makes them a collective intelligence. The shared semantic map IS the product. The more robots, the smarter each one becomes.
A network effect for robot fleets.