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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review.

Luis Pérez¹, Íñigo Rodríguez², Nuria Rodríguez³

¹Fundación PRODINTEC, Avda. Jardín Botánico 1345, 33203 Gijón (Asturias), Spain. lcp@prodintec.com.

Sensors (Basel, Switzerland)

|March 10, 2016

Summary

This review compares machine vision techniques for autonomous robot guidance in factories. It analyzes sensor accuracy, range, processing time, and environmental factors to aid system selection.

Keywords:

3D sensors machine vision part localization perception for manipulation robot guidance robot pose

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Area of Science:

Robotics
Computer Vision
Industrial Automation

Background:

Autonomous robots require visual feedback for navigation, collaboration, and part identification in future factories.
Machine vision techniques are crucial for industrial inspection, quality control, and increasingly for robot guidance.

Purpose of the Study:

To present a comparative review of various machine vision techniques for robot guidance.
To provide background information for researchers and developers in selecting appropriate vision systems.

Main Methods:

Comparative analysis of different machine vision techniques.
Evaluation based on sensor accuracy, range, weight, safety, processing time, and environmental influences.

Main Results:

The choice of vision system is highly dependent on the specific parts to be located or measured.
Analysis covers key performance metrics and operational considerations for each technique.

Conclusions:

This review serves as essential background for selecting optimal machine vision systems for robot guidance.
Informed decisions on vision system technology can enhance robot performance and factory automation.