TVL₁ Planarity Regularization for 3D Shape Approximation

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within. This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy

Comparison of Volumetric Analysis Methods for Machine Tools with Rotary Axes

Confidence in the ability of a production machine to meet manufacturing tolerances requires a full understanding of the accuracy of the machine. However, the definition of “the accuracy of the machine” is open to interpretation. Historically, this has been in terms of linear positioning accuracy of an axis with no regard for the other errors of the machine. Industry awareness of the three-dimensional positioning accuracy of a machine over its working envelope has slowly developed to an extent that people are aware that “volumetric accuracy” gives a better estimation of machine performance. However, at present there is no common standard for volumetric errors of machine tools, although several researchers have developed models to predict the effect of the combined errors. The error model for machines with three Cartesian axes has been well addressed, for example by the use of homogenous transformation matrices. Intuitively, the number of error sources increases with the number of axes present on the machine. The effect of the individual axis geometric errors can become increasingly significant as the chain of dependent axes is extended. Measurement of the “volumetric error” or its constituents is often restricted to a subset of the errors of the Cartesian axes by solely relying on a laser interferometer for measurement. This leads to a volumetric accuracy figure that neglects the misalignment errors of rotary axes. In more advanced models the accuracy of the rotary axes are considered as a separate geometric problem whose volumetric accuracy is then added to the volumetric accuracy of the Cartesian axes. This paper considers the geometric errors of some typical machine configurations with both Cartesian and non-Cartesian axes and uses case studies to emphasise the importance of measurement of all the error constituents. Furthermore, it shows the misrepresentation when modelling a five-axis machine as a three-plus-two error problem. A method by which the five-axis model can be analysed to better represent the machine performance is introduced. Consideration is also given for thermal and non-rigid influences on the machine volumetric accuracy analysis, both in terms of the uncertainty of the model and the uncertainty during the measurement. The magnitude of these errors can be unexpectedly high and needs to be carefully considered whenever testing volumetric accuracy, with additional tests being recommended