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Autonomous AGV Mapping System

A LiDAR-based mapping and localization system for an autonomous industrial guided vehicle.

Year

2024–2026

Status

Prototype

Role

Mapping Software, Sensor Processing, Interface Integration

Duration

Competition & Independent Development

Autonomous AGV Mapping System main interface

Context and objective

This project focuses on real-time mapping, localization and navigation for an industrial AGV. It combines 2D LiDAR scans, wheel odometry, IMU data and QR-based absolute position corrections to build a more reliable understanding of the vehicle's environment.

Challenges and solutions

⚠

Accumulated positioning error

Wheel-based odometry drifts over time. QR landmarks were introduced as known reference points to periodically correct the estimated pose.

⚲

Noisy and moving map points

Raw scans may include temporary obstacles and measurement noise. Filtering and point-age logic help keep the map stable and remove stale points.

Key features

✓
360-degree 2D LiDAR data processing
✓
Polar-to-Cartesian coordinate conversion
✓
ICP scan matching with KDTree and SVD
✓
Encoder and IMU-assisted odometry
✓
QR-based absolute position correction
✓
Obstacle detection and map maintenance
✓
Dijkstra-based path planning
✓
Real-time robot monitoring interface

Tools used in the project

PythonRPLIDARRaspberry PiWebSocketROS 2NumPy

Selected screens and system views

Autonomous AGV Mapping System project screen 1

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