KLNavBot is a cloud-connected autonomous campus delivery robot built around an ESP32 controller, GPS tracking, ultrasonic obstacle detection, and Firebase-backed real-time monitoring. The project combines embedded control, cloud synchronization, and a modern web dashboard to demonstrate a practical autonomous delivery stack for campuses and smart facilities.
- ESP32-based robot control for a two-motor mobile platform
- GPS tracking through a NEO-6M module
- Ultrasonic obstacle detection with fail-safe stopping
- Firebase Realtime Database for live status and command exchange
- Browser-based monitoring and route visualization
- Autonomous campus delivery workflow for robotics and IoT demonstrations
- Real-time tracking of robot position, state, and obstacle status
- Remote manual control through Firebase commands
- Cloud dashboard for live route and robot monitoring
- Secure Firebase rules for public telemetry and authenticated control paths
- MicroPython-based firmware structure for modular ESP32 development
| Path | Purpose |
|---|---|
| firmware/main.ino | ESP32 main loop, WiFi, Firebase polling, GPS upload, obstacle safety |
| firmware/gps_module.cpp | NEO-6M GPS parsing and coordinate conversion |
| firmware/motor_control.cpp | L298N motor driver abstraction for movement commands |
| dashboard/ | Live web dashboard assets |
| firebase/ | Firebase config and security rules |
| docs/ | Architecture and design documentation |
- ESP32 for compute, WiFi, and cloud communication
- NEO-6M GPS for location tracking
- HC-SR04 ultrasonic sensor for obstacle detection
- L298N motor driver for differential drive control
- MPU6050-ready sensor fusion architecture for future IMU stabilization
/robotCommandsstores remote motion commands such asforward,backward,left,right, andstop/robotStatusstores obstacle state, motion state, and heartbeat timestamps/robotGPSstores the latest latitude, longitude, and satellite count/deliveryOTPand admin paths are reserved for authenticated delivery workflows
- Architecture Diagram
- Hardware Architecture
- Software Architecture
- Firebase Data Flow Diagram
- Sensor Fusion Methodology
- Navigation Workflow
- Project Results
- Future Scope
- Configure the ESP32 WiFi credentials in the firmware.
- Set the Firebase project URL and database access rules.
- Flash the firmware files to the ESP32.
- Open the dashboard and confirm that GPS, status, and command updates appear in real time.
KLNavBot is designed to present a complete robotics stack: embedded firmware, sensor integration, cloud telemetry, real-time UI, and an autonomous delivery workflow. It is a compact demo of the kinds of skills used in robotics, embedded systems, autonomous vehicles, and IoT product development.