Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification

Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting component functionality. Thus, material and production costs decrease to maintain the foundry process profitable on the large-scale component supplier market. New measurement methods, such as dense matching techniques, rely on surface texture of casting parts to enable the 3D dense reconstruction of surface points without the need of an active light source as usually applied with 3D scanning optical sensors. This paper presents the accuracy evaluation of dense matching based approaches for casting part verification. It compares the accuracy obtained by dense matching technique with already certified and validated optical measuring methods. This uncertainty evaluation exercise considers both artificial targets and key natural points to quantify the possibilities and scope of each approximation. Obtained results, for both lab and workshop conditions, show that this image data processing procedure is fit for purpose to fulfill the required measurement tolerances for casting part manufacturing processes.

Natural multimodal communication for human–robot collaboration

This article presents a semantic approach for multimodal interaction between humans and industrial robots to enhance the dependability and naturalness of the collaboration between them in real industrial settings. The fusion of several interaction mechanisms is particularly relevant in industrial applications in which adverse environmental conditions might affect the performance of vision-based interaction (e.g. poor or changing lighting) or voice-based interaction (e.g. environmental noise). Our approach relies on the recognition of speech and gestures for the processing of requests, dealing with information that can potentially be contradictory or complementary. For disambiguation, it uses semantic technologies that describe the robot characteristics and capabilities as well as the context of the scenario. Although the proposed approach is generic and applicable in different scenarios, this article explains in detail how it has been implemented in two real industrial cases in which a robot and a worker collaborate in assembly and deburring operations.