ARVISCOPE: Georeferenced Visualization of Dynamic Construction Processes in Three-Dimensional Outdoor Augmented Reality.

Construction processes can be conceived as systems of discrete, interdependent activities. Discrete Event Simulation (DES) has thus evolved as an effective tool to model operations that compete over available resources (personnel, material, and equipment). A DES model has to be verified and validated to ensure that it reflects a modeler’s intentions, and faithfully represents a real operation. 3D visualization is an effective means of achieving this, and facilitating the process of communicating and accrediting simulation results. Visualization of simulated operations has traditionally been achieved in Virtual Reality (VR). In order to create convincing VR animations, detailed information about an operation and the environment has to be obtained. The data must describe the simulated processes, and provide 3D CAD models of project resources, the facility under construction, and the surrounding terrain (Model Engineering). As the size and complexity of an operation increase, such data collection becomes an arduous, impractical, and often impossible task. This directly translates into loss of financial and human resources that could otherwise be productively used. In an effort to remedy this situation, this dissertation proposes an alternate approach of visualizing simulated operations using Augmented Reality (AR) to create mixed views of real existing jobsite facilities and virtual CAD models of construction resources. The application of AR in animating simulated operations has significant potential in reducing the aforementioned Model Engineering and data collection tasks, and at the same time can help in creating visually convincing output that can be effectively communicated. This dissertation presents the design, methodology, and development of ARVISCOPE, a general purpose AR animation authoring language, and ROVER, a mobile computing hardware framework. When used together, ARVISCOPE and ROVER can create three-dimensional AR animations of any length and complexity from the results of running DES models of engineering operations. ARVISCOPE takes advantage of advanced Global Positioning System (GPS) and orientation tracking technologies to accurately track a user’s spatial context, and georeferences superimposed 3D graphics in an augmented environment. In achieving the research objectives, major technical challenges such as accurate registration, automated occlusion handling, and dynamic scene construction and manipulation have been successfully identified and addressed.Ph.D.Civil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60761/1/abehzada_1.pd

Context-Aware Mobile Augmented Reality Visualization in Construction Engineering Education

Recent studies suggest that the number of students pursuing science, technology, engineering, and mathematics (STEM) degrees has been generally decreasing. An extensive body of research cites the lack of motivation and engagement in the learning process as a major underlying reason of this decline. It has been discussed that if properly implemented, instructional technology can enhance student engagement and the quality of learning. Therefore, the main goal of this research is to implement and assess effectiveness of augmented reality (AR)-based pedagogical tools on student learning. For this purpose, two sets of experiments were designed and implemented in two different construction and civil engineering undergraduate level courses at the University of Central Florida (UCF). The first experiment was designed to systematically assess the effectiveness of a context-aware mobile AR tool (CAM-ART) in real classroom-scale environment. This tool was used to enhance traditional lecture-based instruction and information delivery by augmenting the contents of an ordinary textbook using computer-generated three-dimensional (3D) objects and other virtual multimedia (e.g. sound, video, graphs). The experiment conducted on two separate control and test groups and pre- and post- performance data as well as student perception of using CAM-ART was collected through several feedback questionnaires. In the second experiment, a building design and assembly task competition was designed and conducted using a mobile AR platform. The pedagogical value of mobile AR-based instruction and information delivery to student learning in a large-scale classroom setting was also assessed and investigated. Similar to the first experiment, students in this experiment were divided into two control and test groups. Students\u27 performance data as well as their feedback, suggestions, and workload were systematically collected and analyzed. Data analysis showed that the mobile AR framework had a measurable and positive impact on students\u27 learning. In particular, it was found that students in the test group (who used the AR tool) performed slightly better with respect to certain measures and spent more time on collaboration, communication, and exchanging ideas in both experiments. Overall, students ranked the effectiveness of the AR tool very high and stated that it has a good potential to reform traditional teaching methods

Anwendung von Lean-Prinzipien im Erdbau - Entwicklung eines Baustellenleitstands auf Basis von Virtual Reality

Die vorliegende Arbeit befasst sich mit der Entwicklung eines Baustellenleitstands auf Basis von Virtual Reality für den Erdbau unter Berücksichtigung des Lean Management. Hierbei konnte neben der erhöhten Verfügbarkeit von Informationen und deren transparenter Darstellung durch die Anwendung eines digitalen Kanban-Systems eine Steigerung der Produktionsleistung auf der Erdbaustelle nachgewiesen werden

Anwendung von Lean-Prinzipien im Erdbau - Entwicklung eines Baustellenleitstands auf Basis von Virtual Reality

Die vorliegende Arbeit befasst sich mit der Entwicklung eines Baustellenleitstands auf Basis von Virtual Reality für den Erdbau unter Berücksichtigung des Lean Management. Hierbei konnte neben der erhöhten Verfügbarkeit von Informationen und deren transparenter Darstellung durch die Anwendung eines digitalen Kanban-Systems eine Steigerung der Produktionsleistung auf der Erdbaustelle nachgewiesen werden

Affecting Fundamental Transformation in Future Construction Work Through Replication of the Master-Apprentice Learning Model in Human-Robot Worker Teams

Construction robots continue to be increasingly deployed on construction sites to assist human workers in various tasks to improve safety, efficiency, and productivity. Due to the recent and ongoing growth in robot capabilities and functionalities, humans and robots are now able to work side-by-side and share workspaces. However, due to inherent safety and trust-related concerns, human-robot collaboration is subject to strict safety standards that require robot motion and forces to be sensitive to proximate human workers. In addition, construction robots are required to perform construction tasks in unstructured and cluttered environments. The tasks are quasi-repetitive, and robots need to handle unexpected circumstances arising from loose tolerances and discrepancies between as-designed and as-built work. It is therefore impractical to pre-program construction robots or apply optimization methods to determine robot motion trajectories for the performance of typical construction work. This research first proposes a new taxonomy for human-robot collaboration on construction sites, which includes five levels: Pre-Programming, Adaptive Manipulation, Imitation Learning, Improvisatory Control, and Full Autonomy, and identifies the gaps existing in knowledge transfer between humans and assisting robots. In an attempt to address the identified gaps, this research focuses on three key studies: enabling construction robots to estimate their pose ubiquitously within the workspace (Pose Estimation), robots learning to perform construction tasks from human workers (Learning from Demonstration), and robots synchronizing their work plans with human collaborators in real-time (Digital Twin). First, this dissertation investigates the use of cameras as a novel sensor system for estimating the pose of large-scale robotic manipulators relative to the job sites. A deep convolutional network human pose estimation algorithm was adapted and fused with sensor-based poses to provide real-time uninterrupted 6-DOF pose estimates of the manipulator’s components. The network was trained with image datasets collected from a robotic excavator in the laboratory and conventional excavators on construction sites. The proposed system yielded an uninterrupted and centimeter-level accuracy pose estimation system for articulated construction robots. Second, this dissertation investigated Robot Learning from Demonstration (LfD) methods to teach robots how to perform quasi-repetitive construction tasks, such as the ceiling tile installation process. LfD methods have the potential to be used in teaching robots specific tasks through human demonstration, such that the robots can then perform the same tasks under different conditions. A visual LfD and a trajectory LfD methods are developed to incorporate the context translation model, Reinforcement Learning method, and generalized cylinders with orientation approach to generate the control policy for the robot to perform the subsequent tasks. The evaluated results in the Gazebo robotics simulator confirm the promise and applicability of the LfD method in teaching robot apprentices to perform quasi-repetitive tasks on construction sites. Third, this dissertation explores a safe working environment for human workers and robots. Robot simulations in online Digital Twins can be used to extend designed construction models, such as BIM (Building Information Models), to the construction phase for real-time monitoring of robot motion planning and control. A bi-directional communication system was developed to bridge robot simulations and physical robots in construction and digital fabrication. Through empirical studies, the high accuracy of the pose synchronization between physical and virtual robots demonstrated the potential for ensuring safety during proximate human-robot co-work.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169666/1/cjliang_1.pd

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

Uma plataforma concetual para a integração de realidade aumentada e BIM nos sistemas de gestão de qualidade de empresas de construção

Dissertação para obtenção do Grau Mestre em Engenharia Civil – Perfil de ConstruçãoUm dos principais benefícios da adoção de Sistemas de Gestão de Qualidade (SGQ) por parte das empresas de construção relaciona-se com a diminuição dos custos associados à ocorrên-cia de não conformidades (NC) ao longo dos seus projetos. No entanto, as dificuldades experi-mentadas pelas Pequenas e Médias Empresas (PMEs) na implementação de SGQ eficazes tradu-zem-se habitualmente num aumento substancial da ocorrência de NC durante os seus projetos de construção. A ocorrência de NC durante os projetos de construção é recorrentemente associada à ina-dequada comunicação entre os diversos intervenientes dos processos de construção. A utilização do Building Information Modeling (BIM) como ferramenta de comunicação entre os diversos intervenientes da indústria da construção (IC) tem sido apontada como a resposta aos crónicos problemas de comunicação que caracterizam a indústria. Contudo, a sua utilização no contexto físico dos locais de obra continua a carecer de ferramentas que permitam a visualização da infor-mação contida nos modelos BIM no espaço físico dos utilizadores. O rápido desenvolvimento de novas tecnologias de visualização, entre elas a Realidade Aumentada (RA), permitirá transpor toda a informação contida nos modelos BIM para o contexto físico dos locais de obra. Assim, o presente trabalho propõe uma plataforma concetual baseada na integração de RA e modelos BIM nos SGQ das empresas de construção. O objetivo da plataforma é eliminar as deficiências e lacunas evidenciadas pelos SGQ no processo de gestão de não conformidades (GNC). Previamente ao seu desenvolvimento, os requisitos funcionais da plataforma teriam de ser estabelecidos. Deste modo, foi efetuada uma análise dos processos incluídos na GNC através da técnica Integrated Definition for Function Modeling (IDEF0), resultando da análise o estabeleci-mento dos requisitos funcionais da plataforma. Esta análise baseou-se em um caso de estudo res-peitante aos processos incluídos no SGQ de uma empresa de construção portuguesa. Com os requisitos funcionais estabelecidos, foi desenvolvida a plataforma com recurso a uma abordagem de systems thinking. Com a integração da plataforma proposta nos atuais SGQ perspetiva-se um aumento da eficácia dos processos incluídos na GNC, assim como uma melhor aceitação dos SGQ por parte dos intervenientes da IC