Warehouse Robotics
WRIE — Warehouse Robotics Intelligence Engine
Provide your warehouse layout and robot specs, and it autonomously simulates your entire operation in a browser, powered by production-grade C++ fleet management. Open-source, free, works with ANY robot. One Docker command.
# Live Fleet Simulation
8 Addverb robots navigating a warehouse grid. Each robot has unique specs, speed, and battery from YAML configs.
# By The Numbers
# Architecture
Your warehouse JSON + robot YAMLs
│
┌───────────────────────────────────────┐
│ C++ Fleet Manager (15Hz loop) │ ← The brain
│ Pathfinding, task assignment, │
│ collision avoidance, battery mgmt │
└───────────────────┬───────────────────┘
│
┌───────────────────────────────────────┐
│ Python API (152+ REST + WebSocket) │ ← The interface
│ Orders, tasks, WMS, VDA5050, │
│ inventory, maintenance, charging │
└───────────────────┬───────────────────┘
│
┌───────────────────────────────────────┐
│ React Dashboard (browser) │ ← What you see
│ 2D fleet view + 3D Three.js scene │
│ Live robot positions via WebSocket │
└───────────────────────────────────────┘
│
┌───────────────────────────────────────┐
│ Gazebo Fortress (optional) │ ← Physics layer
│ 3D world, LiDAR, real physics │
│ 7 robot models by manufacturer │
└───────────────────────────────────────┘# 13 Capabilities
Everything a warehouse robotics simulator needs. No vendor lock-in.
Design a Warehouse
Load a JSON warehouse map or use the HTML5 visual designer. Place shelves, docks, charging stations, conveyors, sorter lanes. 9 pre-built layouts included.
Pick Your Robots
Drop in YAML configs: Addverb Dynamo (1500kg forklift), Zippy10 (30kg conveyor bot), or define your own. 7 types ready, mix AMRs + AGVs + forklifts in one fleet.
Run the Simulation
C++ engine runs fleet management at 15Hz — pathfinding, task assignment, collision avoidance, battery management. 3D browser visualization via React Three Fiber.
Compare Scenarios
FIFO vs nearest-robot? 10 robots vs 30? Create scenarios, run them, compare side-by-side with charts. KPIs in 30 seconds.
Connect to Your WMS
SAP, Odoo, or webhook adapters pull real orders from your warehouse management system. Dead letter queue with automatic retry for failed orders.
VDA5050 Standard
Industry-standard protocol used by Addverb, KUKA, and others. Send orders and receive status updates via MQTT. Simulation designs are compatible with real deployments.
Scale to 100+ Robots
MAPF solver handles 100+ concurrent robots without deadlocks. CBS (optimal) for small fleets, PIBT (fast) for large fleets. Real-time congestion tracking.
Inventory & Material Handling
Full WCS: conveyor belts, high-speed sorters, 5 lane types, package tracking. Inventory management with receive, pick, transfer, cycle count, replenishment, ABC analysis.
Predictive Maintenance
Every robot component has an MTBF model with degradation curves. “Motor has 39% chance of failing in next 500 hours.” Fleet impact calculator for maintenance scheduling.
Human-Robot Coexistence
Add human workers to the simulation — they create dynamic safety zones. Robots yield, reroute, or stop when humans are nearby. Measure throughput impact of shift changes.
Smart Charging
4 strategies: opportunistic, scheduled, priority, balanced. Battery degradation over charge cycles. Energy demand forecasting for the next 2 hours.
Robot Localization Recovery
io-gita recovers lost robot position in 0.008ms via KDTree spatial matching. 97.2% zone accuracy, 5-phase recovery. Works without GPS or pre-mapped SLAM.
ROS2 Integration
nav2 bridge: send navigation goals, get robot poses from ROS2 odometry. HAL abstraction lets you swap between simulated and real robots without code changes.
# Robot Fleet
7 robot types organized by manufacturer. Extensible via YAML.
| Robot | Payload | Speed |
|---|---|---|
| Addverb Dynamo | 1500kg | 1.5 m/s |
| Addverb Veloce | 240kg | 1.5 m/s |
| Addverb Quadron | 50kg | 4.0 m/s |
| AMR500 | 500kg | 0.8 m/s |
| Zippy10 | 30kg | 1.4 m/s |
| DiffDrive AMR | 500kg | 2.0 m/s |
| Uni AGV | 30kg | 1.4 m/s |
# Full Stack
| C++ Core | C++17, CMake, vcpkg · FleetManager 15Hz · A*, QuadTree, NodeReservation · BehaviorTree engine · TCP Protocol V1 + CRC32 |
| Python API | FastAPI · 152+ REST + WebSocket · Pydantic v2 · API key auth · CORS |
| WES | OrderGenerator (Poisson) · TaskGenerator · WaveEngine · KPITracker |
| WMS/ERP | SAP, Odoo, Webhook adapters · OrderTranslator · DLQ with retry |
| WCS | ConveyorController · SorterEngine · LaneManager · PackageTracker |
| VDA5050 | MQTT Gateway · v2/v3 message models · AGV state machine · Instant actions |
| MAPF | CBS (optimal, small fleets) · PIBT (fast, 100+ robots) · Congestion tracker |
| Frontend | React 19 · TypeScript · Vite · React Three Fiber · Tailwind CSS |
| Simulation | Gazebo Fortress (gz-sim7) · LiDAR, barcode, conveyor plugins · 7 SDF robot models |
| Infra | Docker Compose (8 services) · MongoDB · Redis · InfluxDB · RabbitMQ · Grafana · Mosquitto |
| Testing | 1500+ tests · gtest (C++) · pytest (Python) · Gazebo integration · Skip guards for sandboxed envs |
# Who It's For
# What It's NOT
This is a simulation, not a production fleet controller. The C++ FMS is production-grade architecture, but deploying to a real warehouse needs sensor integration, safety certification, and field testing that no simulator replaces. The value is in proving your design works BEFORE you spend money building it.