# Controlling AGV While Docking Based on the Fuzzy Rule Inference System

**Authors:** Damian Grzechca, Łukasz Gola, Michał Grzebinoga, Adam Ziębiński, Krzysztof Paszek, Lukas Chruszczyk

PMC · DOI: 10.3390/s25196108 · Sensors (Basel, Switzerland) · 2025-10-03

## TL;DR

This paper presents a software-based solution to improve the docking accuracy of AGVs using a fuzzy logic controller, enhancing automation in industrial settings.

## Contribution

The novel use of a Takagi-Sugeno FLC as a gain-scheduling lookup table improves docking precision without new hardware.

## Key findings

- A two-stage strategy improves AGV docking accuracy using a fuzzy logic controller.
- The method achieves repeatable docking within acceptable industrial tolerances.
- The approach handles positional uncertainty and environmental variations effectively.

## Abstract

Accurate docking of Autonomous Guided Vehicles (AGVs) is a critical requirement for efficient automated production systems in Industry 4.0, particularly for collaborative tasks with robotic arms that have a limited working range. This paper introduces a cost-effective software-upgrade solution to enhance the precision of the final docking phase without requiring new hardware. Our approach is based on a two-stage strategy: first, a switch from a global dead reckoning system to a local navigation scheme, is triggered near the docking station; second, a dedicated Takagi-Sugeno Fuzzy Logic Controller (FLC), guides the AGV to its final position with high accuracy. The core novelty of our FLC is its implementation as a gain-scheduling lookup table (LUT), which synthesizes critical state variables—heading error and distance error—from limited proximity sensor data, to robustly handle positional uncertainty and environmental variations. This method directly addresses the inadequacies of traditional odometry, whose cumulative errors become unacceptable at the critical docking point. For experimental validation, we assume the global navigation delivers the AGV to a general switching point, near the assembly station with an unknown true pose. We detail the design of the fuzzy controller and present experimental results that demonstrate a significant improvement, achieving repeatable docking accuracy within industrially acceptable tolerances.

## Full-text entities

- **Chemicals:** AGV (-)

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12526989/full.md

## References

34 references — full list in the complete paper: https://tomesphere.com/paper/PMC12526989/full.md

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Source: https://tomesphere.com/paper/PMC12526989