Deep learning methods have revolutionized computer vision since the appearance of AlexNet in 2012. Nevertheless, 6 degrees of freedom pose estimation is still a difficult task to perform precisely. Therefore, we propose 2 ensemble techniques to …
In this paper, an innovative algorithm for averaging a set of multivariate time series with different lengths based on Constrained Dynamic Time Warping (CDTW) is proposed. This approach relies on the CDTW to provide the non-linear alignment of the …
This study describes the software methodology designed for systematic benchmarking of bipedal systems through the computation of performance indicators from data collected during an experimentation stage. Under the umbrella of the European project …
Deep learning methods have been successfully applied to image processing, mainly using 2D vision sensors. Recently, the rise of depth cameras and other similar 3D sensors has opened the field for new perception techniques. Nevertheless, 3D …
This study aims to evaluate different combinations of features and algorithms to be used in the control of a prosthetic hand wherein both the configuration of the fingers and the gripping forces can be controlled. This requires identifying machine …
This article deals with the 2D image-based recognition of industrial parts. Methods based on histograms are well known and widely used, but it is hard to find the best combination of histograms, most distinctive for instance, for each situation and …
While Industrial robots are very successful in many areas of industrial manufacturing, assembly automation still suffers from complex time consuming programming and the need of dedicated hardware. ABB has developed YuMi, a collaborative inherently …