NeuroSync Robotics Platform

Real-time neuromorphic robot control and monitoring platform with spiking neural networks and ROS2 integration

---

Overview

NeuroSync is an interactive real-time visualization and control portal for neuromorphic robot systems powered by spiking neural networks (SNNs). It bridges the gap between neuroscientific research and practical robotics, providing engineers and researchers with an intuitive interface to monitor, control, and analyze robot behavior driven by biologically-inspired neural controllers.

---

Screenshots

Landing Page

Hero section - Real-Time Control, SNN-Powered, and Safety First feature highlights.

Project metadata: author, CC-BY-NC-4.0 license, and GitHub repository link.

Robot Fleet Dashboard

Fleet overview showing Manipulator Alpha, Mobile Base Beta, and Dual-Arm Gamma with live battery, temperature, CPU, and signal metrics. 95% connection quality across the fleet.

Manipulator Alpha - Command Console

Per-robot control panel for the 6-DOF collaborative manipulator. ROS2 Command Console accepts raw JSON payloads. Emergency Stop always present in the header.

---

Key Features

Feature	Description
Real-Time Monitoring	Live telemetry from multiple robots with sub-500ms latency updates
Joint-Level Control	Precise 6-DOF joint control with position feedback visualization
Command Console	Advanced ROS2 command interface accepting raw JSON payloads
Motion Library	Predefined motion sequences executable with a single interaction
Fleet Management	Monitor and command multiple robots from a unified dashboard
Neuromorphic Integration	SNN controller backends with Lyapunov-stable surrogate gradient training
Safety Architecture	Emergency stop, connection health monitoring, and failsafe controls
Responsive Design	Fully functional across desktop, tablet, and mobile viewports

---

Architecture

---

Installation

Prerequisites

• Node.js 18+ and pnpm
• Python 3.10+
• ROS2 Humble or later (optional, for real hardware)
• Git

Frontend

git clone https://github.com/Nihara-D/neuromorphic-snn-controller-research-env.git
cd neuromorphic-snn-controller-research-env
pnpm install
pnpm dev
# → http://localhost:3000

Neuromorphic Backend

uv sync
uv run python scripts/spike_encoder.py
uv run python scripts/snn_surrogate_gradient.py
uv run python scripts/lyapunov_stability.py

---

Usage

Navigate to http://localhost:3000/dashboard to view all connected robots, system health metrics, and connection status. Click any robot to access its individual control panel.

Joint control example:

Joint "manipulator_joint_1": 90.0°  // position feedback: 89.8°

Command console JSON format:

{
  "type": "joint_control",
  "payload": {
    "joints": {
      "joint_1": 45,
      "joint_2": 90,
      "joint_3": 120
    }
  }
}

---

API Reference

# Command execution
POST /api/robots/{robotId}/command

# Motion sequences
POST /api/robots/{robotId}/motions

# Real-time WebSocket bridge
WS ws://localhost:3000/api/ros/websocket?robot_id={robotId}

---

Configuration

# .env.local
ROS2_BRIDGE_HOST=localhost
ROS2_BRIDGE_PORT=8000
ROS2_NAMESPACE=/robot
ROBOT_UPDATE_INTERVAL=500
TELEMETRY_BUFFER_SIZE=1000
ENABLE_AUTH=false

To connect real robots, set USE_MOCK_DATA=false and configure the ROS2 bridge variables above.

---

Technology Stack

Layer	Technology	Purpose
Frontend	Next.js 16, React 19, TypeScript 5.7	Web UI and visualization
Styling	Tailwind CSS 4, shadcn/ui	Component design system
State	Zustand	Real-time state management
Charts	Recharts	Telemetry visualization
Backend	Next.js API Routes	Command handling and ROS2 bridge
Neuromorphic	Python 3.10+, NumPy	SNN controller and training
Communication	WebSockets, HTTP/REST	Real-time data and commands

---

Performance

Metric	Value
Command execution	50 – 200 ms
Telemetry update	100 – 500 ms
UI render	< 16 ms (60 FPS)
Network latency (LAN)	2 – 20 ms

---

Project Structure

---

Research Background

• Leaky Integrate-and-Fire Neurons
• Surrogate Gradient Methods for SNN Learning
• Lyapunov Stability for Nonlinear Systems
• Neuromorphic Computing in Robotics

---

License

Licensed under CC-BY-NC-4.0 - free to share and adapt for non-commercial purposes with attribution. See LICENSE.

---

Citation

@software{neurosync2026,
  author  = {Randini, Nihara},
  title   = {NeuroSync Robotics Platform},
  year    = {2026},
  url     = {https://github.com/Nihara-D/neuromorphic-snn-controller-research-env},
  license = {CC-BY-NC-4.0}
}

---

Contact

Nihara Randini - shniharard@gmail.com - @Nihara-D

Open an Issue

---

Version 1.0.0 - May 2026 - Part of the Neuromorphic SNN Controller Research Environment