🔎 Overview

This project aimed to upgrade an existing Autonomous Guided Vehicle (AGV) used for transporting items from the sub-store to the assembly area in Variosytems. The earlier system had limited navigation adaptability, lacked real-time weight measurement, and relied on blocking delays that reduced responsiveness. The enhanced version integrates a PID-controlled navigation, load cell with calibrated storage, and adaptive white-zone detection, along with a manual override option and non-blocking timers for real-time operation.

Currently, I am developing a robust and adaptive navigation system that enables the AGV to:

• Visit any selected combination of stops (e.g., A, C, D)
• Optimize route to avoid unnecessary paths or backtracking

This logic uses marker counting, junction detection with IR arrays, and path planning (via pre-defined route maps and traversal algorithms). By dynamically selecting stops and executing turns based on marker counts, the AGV will expand into a scalable, route-planning capable transport system.

🔗 GitHub Repository: ‣

✨ Features

• Real-time weighing with calibrated load cell
• PID-based line following for smooth navigation
• Adaptive white-zone detection with turning logic
• Manual override via pushbuttons
• Non-blocking timers for responsive control

⚙️ System Architecture

🛠 Workflow

1. PID algorithm used for line-following.
2. White-zone detection added adaptive turning.
3. Load cell integrated with calibration stored in EEPROM.
4. Blocking delays replaced with timers for real-time control.