AMR Fleet Real-Time Simulator

A high-performance industrial digital twin simulation for Autonomous Mobile Robots (AMRs), built using a native C++ simulation engine compiled to WebAssembly (WASM) and a React-based presentation layer.

Live Demo

Access the Live Simulation

Project Overview

Modern automated manufacturing and logistics environments require deterministic, low-latency coordination for multi-robot fleets. This project models a warehouse floor digital twin to evaluate runtime kinematics, path planning concepts, and autonomous power management under constrained conditions.

To achieve industrial-grade performance without server infrastructure overhead, the heavy computational logic runs entirely on the client-side edge via WebAssembly, decoupling physical calculations from the UI rendering thread.

Core Engineering Features

• C++ WebAssembly Core: The simulation engine is written in native C++ and compiled via Emscripten, enabling heavy continuous-time math and matrix processing to execute directly in the browser with near-native speed.
• Deterministic State Machines: Robots independently manage their operational states (IDLE, MOVING, CHARGING) based on real-time telemetry and triggers.
• Continuous-Time Kinematics: Motion calculations rely on delta-time scaling, ensuring physics updates remain frame-rate independent regardless of client hardware performance.
• Client-Serverless Architecture: Completely serverless design running entirely in the browser, eliminating hosting latency, WebSocket overhead, and backend idle costs.

State Machine & Autonomous Charging Mechanics

The simulation incorporates a robust safety and energy management lifecycle:

1. IDLE State: Robots stand by at designated grid nodes, continuously evaluating task queues and battery levels.
2. MOVING State: Upon receiving a task coordinate, vector kinematics calculate optimal displacement per frame, steadily depleting energy reserves per second of motion.
3. Autonomous Fail-Safe & CHARGING State:

• Critical Threshold: If a robot's battery drops below 20%, an automated fail-safe overrides current instructions and re-routes the unit back to the charging dock at coordinate (0,0).
• Stationary Regeneration: Upon docking, spatial movement is paused while energy is regenerated using continuous-time equations until capacity reaches 100%.
• State Recovery: Once fully charged, the robot automatically transitions back to IDLE, ready for new dispatch assignments.

System Architecture

+-------------------------------------------------------+
|                      Browser                          |
|                                                       |
|  +--------------------+      cwrap / Memory Bridge    |
|  |   React Frontend   | <---------------------------+ |
|  |  (Canvas 60 FPS)   |                             | |
|  +--------------------+                             | |
|            ^                                        | |
|            | requestAnimationFrame                  v |
|            |                              +-----------+---+
|            +----------------------------> | C++ Engine    |
|                                           | (WASM Binary) |
|                                           +---------------+
+-------------------------------------------------------+

Local Development & Compilation

Prerequisites

• Node.js (v18 or higher)
• Emscripten SDK (emsdk) for C++ compilation

1. Clone the Repository

git clone https://github.com/your-username/AMR-WASM-Simulator.git
cd AMR-WASM-Simulator

2. Compile C++ to WebAssembly

Activate your Emscripten environment, then execute the build script to compile the core engine:

bash core_engine/build.sh

(This updates engine.js and engine.wasm inside web_ui/public/)

3. Run the Frontend UI

cd web_ui
npm install
npm run dev

License

Distributed under the MIT License. See LICENSE for more information.

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Developed by Dedy Van Hauten