Systems are known for determining vehicle wheel alignment, in particular for a motor vehicle, which enable the automatic measuring of one or more characteristic angles of the wheels, for example, the convergence and camber angles, in order to check the correct reciprocal alignment of the wheels. In fact, as is known, incorrect alignment can cause excessive or uneven tyre wear and also cause driving and vehicle stability problems.
In general, systems for determining vehicle wheel alignment are configured to detect the orientation of the plane of each wheel with respect to a single set of three orthonormal axes taken as reference (it should be noted that the “plane of the wheel” is intended as the plane on which the outer side surface of the wheel lies), so as to enable suitable corrective actions to be taken to restore the reciprocal alignment of the wheels.
In particular, some systems envisage the use of detection elements for the characteristic angles, or in any case suitable sensitive elements, directly connected to the wheels of the vehicle via special mounting devices (so-called “clamps”), in order to identify the set-up geometry; in this case, great care is needed in mounting them on the wheels in order to avoid damaging delicate parts.
Other systems move the observation point outside of the vehicle, so as to define a fixed reference system with respect to that of the set-up, by means of observing angular variations of the wheels through one or more image acquisition devices unconstrained by the orientation of the vehicle. In particular, some systems contemplate positioning the image acquisition devices directly on the car lift (able to raise the vehicle under observation in a known manner); other systems contemplate positioning the same image acquisition devices on structures that are fixed or independently movable, located at a distance from and free with respect to both the vehicle and the car lift. In the first case, the image acquisition devices follow the movements of the car lift, but, because of this, they must dynamically compensate distortion; in the second case, the image acquisition devices must lock onto the car lift via controlled movements so as to remain aimed on the wheels, but do not need to compensate distortion.
Usually, such systems use suitable targets mounted on the wheels of the vehicle so as to highlight their rotation and position in space.
In particular, the targets have a flat surface depicting two-dimensional images of various shapes that can be recognised by the image acquisition devices. A processing device coupled to the image acquisition devices generally performs a so-called “best fit” operation on the geometries of the two-dimensional images identified on a generally flat surface forming part of the real target and the two-dimensional images that the image acquisition devices provide in their reference system. This operation enables the spatial orientation of the target to be determined dynamically and therefore to define elementary rotations and translations regarding the linear and angular movement of each wheel within a single reference system (for example, the vehicle's reference system). Afterwards, these elementary rotations and translations, opportunely linked together, are used for the definition of further, more complex rotations and translations that more specifically concern the vehicle's set-up and alignment characteristics.
For example, WO 2008/143614 A1 discloses an alignment determining system that contemplates the use of targets connected to the wheels of a vehicle. Each target is formed by a set of two-dimensional target elements (in particular, having the form of circles), arranged on multiple planes, mutually parallel to each other or forming a preset angle. The system provides for the identification of the target elements on their associated planes from the acquired images and the implementation of “best fit” algorithms, for example, the mean square mathematical algorithm, to determine the orientation of the targets with respect to a reference system.
However, neither does this solution depart from the traditional ones, as it maintains a typically two-dimensional analytical approach (by means of the best fit operation, i.e. a mathematical and not a geometrical solution), considering the displacement of each individual point identified in the acquired images on the associated plane with respect to the configuration of the real target. Accordingly, even this solution does not allow an increase in measurement resolution to be achieved for a given size of the targets.
Although advantageous in certain aspects, known systems have the drawback of requiring a stereo system for image acquisition, which entails the presence of a plurality of image acquisition devices and acquired images for each target observed. Alternatively, in the case of using a sole image acquisition device, it becomes necessary to perform a suitable recognition procedure for the orientation of the target with respect to the sole image acquisition device, by means of observing the target during suitable movements of the vehicle (for example, forwards and backwards, the so-called “run-out” operation), or during suitable movements of the target itself.
In addition, acquisition of the geometrical characteristics of the two-dimensional target becomes difficult as the inclination of the target changes, resulting in inconsistency in the accuracy of the measurements taken.
Furthermore, in known systems that contemplate the identification of target elements as geometric points on a surface, measurement precision can be compromised in the case where one or more of these target elements are hidden or, in any case, cannot be seen by the image acquisition devices.
The need is therefore felt in this field for developing a system for determining the orientation of vehicle wheels that provides greater resolution and precision in angle measurements, does not contemplate the need to perform specific vehicle displacement manoeuvres in order to identify the orientation of the targets and that is also of simple and economic implementation.
USPTO Backgrounds
USPTO Backgrounds