Screw axis measurement methods obtain a precise identification of the physical reality of the industrial robots’ geometry. However, these methods are in a clear disadvantage compared to mathematical optimisation processes for kinematical parameters. That’s because mathematical processes obtain kinematical parameters which best reduce the robot errors, despite not necessarily representing the real geometry of the robot. This paper takes the next step at the identification of a robot’s movement from the identification of its real kinematical parameters for the later study of every articulation’s rotation. We then obtain a combination of real kinematic and dynamic parameters which describe the robot’s movement, improving its precision with a physical understanding of the errors.
This paper presents a comparison of different techniques to capture nominal data for its use in later verification and kinematic parameter identification procedures for articulated arm coordinate measuring machines (AACMM). By using four different probing systems (passive spherical probe, active spherical probe, self-centering passive probe and self-centering active probe) the accuracy and repeatability of captured points has been evaluated by comparing these points to nominal points materialized by a ball-bar gauge distributed in several positions of the measurement volume. Then, by comparing these systems it is possible to characterize the influence of the force over the final results for each of the gauge and probing system configurations. The results with each of the systems studied show the advantages and original accuracy obtained by active probes, and thus their suitability in verification (active probes) and kinematic parameter identification (self-centering active probes) procedures.
This paper presents a method of correcting the effects caused by refraction phenomena in an optical measurement system. The correction algorithm proposed can be applied in many different photogrammetric applications affected by these effects. To validate this algorithm, a foot sole optical measurement system that uses several cameras to build a mesh of a foot sole has been used. This measurement system has six cameras that are protected by a safety glass that separates the cameras from the foot to be measured. The safety glass produces an air-glass-air interface that causes the refraction phenomena, producing deformations in the images. Due to the deformations it is impossible to obtain reliable metric information of the images captured using the measurement system. The developed correction algorithm is based on a grid layout and associated polynomials and makes it possible to correct the deformations and extract accurate metric information.