Fernando Moreu is an Associate Professor at the Department of Civil, Construction, and Environmental Engineering (CCEE) at the University of New Mexico (UNM). He holds courtesy appointments in the Departments of Electrical & Computer Engineering, Mechanical Engineering, and Computer Science at UNM and the founder and director of the Smart Management of Infrastructure Laboratory (SMILab). Prof. Moreu’s research interests include structural dynamics and control, structural health monitoring, wireless smart sensor networks, cyber-physical systems, computer vision, augmented reality, unmanned aerial systems, bridge engineering, and aerospace operations. Prof. Moreu received his MS and PhD degrees in structural engineering from the University of Illinois at Urbana-Champaign (2005 and 2015, respectively). He was the 2022 outstanding junior faculty researcher award at the UNM School of Engineering. Prof. Moreu’s projects are funded by the DOE, NSF, ONR, NAS, US DOT, TRB, and the commercial sector. He is a registered Professional Engineer since 2010. Prof. Moreu is the current Secretary of the ASCE Engineering Mechanics Institute (EMI) Technical Committee in Structural Health Monitoring and Control (SHMC) (2023-2026); the chair of ASCE EMI Education Committee (2024-2027); and the current vice chair of the Society for Experimental Mechanics Technical Division of Dynamics of Civil Structures (2025-2027).
This seminar summarizes human-computer interfaces for quality inspection aided by robotics applications. The objective of this research is to enhance human decision-making with Artificial-Intelligence (AI) and machine-enabled visual analysis. Applications include using Augmented Reality (AR) systems to enable a standalone human interface for automatic defect detection integrating an image-based pattern recognition algorithm in the headset’s platform. The interface quantifies anomalies in the pixel units using a horizontal measurement algorithm improved by the edge gradient analysis and employs a nonstationary pixel unit conversion algorithm to translate the size of anomalies to the engineering units. Additionally, human interfaces for intuitive robot programming are presented. This seminar also describes a new interactive interface for intuitive robot programming that allows humans to adjust the kinematic controller’s parameters or use a different outer-loop controller as an alternative to the time-consuming adjustments of the holograms. Automatic robot control in human proximity is examined where human intention prediction is essential for safe robot planning. This automated control with the AR interface open a bi-lateral communication line between humans and robots. The practical application and validation of the model is examined through experiments related to inspections and manufacturing involving human
upper limb movement in interaction with robots.