Among additive manufacturing processes, wire arc additive manufacturing (WAAM) is one of the most promising methods for manufacturing complex near-net-shape parts, as it allows the layer-by-layer deposition of welded material at a high deposition rate. However, this technology is highly dependent on deposition conditions and thermomechanical phenomena during the process. Therefore, process simulation could be used to analyse the effects of different deposition parameters on the thermomechanical results to optimise the process. However, as the computing time required for this study may become prohibitive, a dedicated strategy is needed to reduce it while maintaining a good level of accuracy. In this study, only the thermal analysis of the process is investigated. An efficient metamodel based on B-spline entities is developed to emulate the thermal response of the WAAM process when building a mild steel four-layer wall structure. Thanks to B-spline entities, the temperature profile at different locations is approximated as a function of a subset of deposition parameters of WAAM process, and the results are compared with the simulated temperature profile resulting from a validation dataset.

Amethod for non-rigid image registration that is suitable for large deformations is presented. Conventional registration methods embed the image in a B-spline object, and the image is evolved by deforming the B-spline object. In this work, we represent the image using B-spline and deform the image using a composition approach. We also derive a computationally efficient algorithm for calculating the B-spline coefficients and gradients of the image by adopting ideas from signal processing using image filters. We demonstrate the application of our method on several different types of 2D and 3D images and compare it with existing methods.

This paper aims to represent a human's upper body motion using a humanoid robot. As a robot has different physical limitations than a human, we present a method that can filter the trajectories to meet the limitations. The filtering can be used directly and also can be used as a constraint for optimization. It will be shown to be applicable both offline and online. Many physical attributes, namely angle, collision, velocity, and dynamic torque, are represented as B-spline explicit functions. The B-spline coefficients are then calculated to limit the physical attributes. This explicit method can guarantee that many limits are met. Hence, it is better than many methods that only reduce such physical attributes using objective functions.

Today, in robot applications continuous paths often result from CAD or other planning tools. We present here an approach to the question that has been discussed for a long time, i.e. how to approximate a given path by a second one in such a way that the latter lies in a tube of given radius ε around the first. The approximation should be a (normally cubic) spline with a small number of breakpoints. The strategy is based on algorithms used in “computer aided geometric design” and is applied to examples from industrial and surgical robotics.