Open AccessDesign and Assessment of a Machine Vision System for Automatic Vehicle Wheel Alignment
Author(s) -
Rocco Furferi,
Lapo Governi,
Yary Volpe,
Monica Carfagni
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/55928
Subject(s) - machine vision , automotive industry , camber (aerodynamics) , scanner , computer science , automotive engineering , computer vision , engineering , artificial intelligence , structural engineering , aerospace engineering
Wheel alignment, consisting of properly checking the wheel characteristic angles against vehicle manufacturersʹ specifications, is a crucial task in the automotive field since it prevents irregular tyre wear and affects vehicle handling and safety. In recent years, systems based on Machine Vision have been widely studied in order to automatically detect wheels’ characteristic angles. In order to overcome the limitations of existing methodologies, due to measurement equipment being mounted onto the wheels, the present work deals with design and assessment of a 3D machine vision‐based system for the contactless reconstruction of vehicle wheel geometry, with particular reference to characteristic planes. Such planes, properly referred to as a global coordinate system, are used for determining wheel angles. The effectiveness of the proposed method was tested against a set of measurements carried out using a commercial 3D scanner; the absolute average error in measuring toe and camber angles with the machine vision system resulted in full compatibility with the expected accuracy of wheel alignment systems