The overall goal of this project is to build local and regional communities to provide anticipatory guidance for (a) disabled-led technology development and (b) community articulation of values in developing disability-forward technological futures.
This project was focused on the design of an affordable housing unit that can address the challenges of sustainable development. The design was also developed for prefabrication in the factory setting through optimized modularization for logistics purposes including on-site installation and transportation across multiple states.
The adoption of 3D concrete printing (3DCP) requires a new generation of construction workforce who are skilled with fundamental knowledge in these topics and beyond, catered to worker type, education and skill level. The goal of this project is to develop fundamental 3DCP training for the industry, placed into a broader, multifaceted curriculum, for the education of 3D concrete printing (3DCP) used in the design and construction of affordable housing.
This project combines the areas of human-computer interaction (HCI) with construction robotics. Seven junior students from the computer science department specialized in HCI collaborated closely with two graduate students in construction engineering in the ARCADE lab to integrate a ground robot (Husky by Clearpath) and a drone (Tello Edu by DJI) to enable collaboration between two robotic agents on construction sites.
The goal of this 4-VA collaborative research was to establish partnership between female junior faculty at Virginia Tech and George Mason University to conduct educational research on STEM pathways of robotics and artificial intelligence. The research team worked on a ground robot platform i.e. Husky robot by Clearpath and an Unmanned Aerial Vehicle (UAV) i.e. Mavic 3 Pro by DJI, to address research questions.
This project aims to examine the challenges of human-robot partnership in the inspection and monitoring of industrialized construction. The construction industry in the United States faces two significant issues: declining productivity over the years and a lack of automation compared to other industries. To address these problems, construction automation using robots has the potential to improve productivity and efficiency.
This convergent research employs the joint perspectives of construction engineering, human factors psychology, and robot control and autonomy to advance the fundamental understanding of future construction progress monitoring work. Nearly $1.3 trillion worth of structures are constructed each year in the U.S., while more than 53% of typical construction projects are behind schedule, and more than 66% suffer from cost overruns. Construction progress monitoring incorporates a set of regular inspections of construction work to prevent schedule delays and unpredicted costs or rework.
Digital twinning is the mapping of a physical asset to a digital platform. Digital twin approach is one of the latest technologies to emerge from Industry 4.0. In this process, physical objects and systems are recreated on a virtual interface and as a result, a fully developed digital replica is constructed for future testing, development, and experimentation.
Environmental disasters, such as storms, wild fires, hurricanes, and oil spills, displace and disrupt the lives of millions of Americans every year. For example, in 2018, California wildfires caused the evacuation of 50,000 people; in 2005, Hurricane Katrina destroyed an estimated 300,000 homes leaving more than 1 million people homeless; and more recently in 2017, Hurricane Maria damaged more than 60,000 homes and left 450,000 customers without power (Fig. 1 [1]). Such disasters have two major impacts: • Disasters have a profound psychological impact.
Drones have been, for long, under the scrutiny of building researchers. Drones can reach places where it is difficult or unsafe for humans to reach, such as building facades, under the bridge deck, etc. However, most research is on non-contact inspection, i.e., they collect data through cameras and other sensors. This project evaluates the potential of using drones or Unmanned Aerial Systems (UAS) for contact-based inspections of buildings that require precise localization and path planning.
