FW-HTF-P: Inspector Assistant Robot for Future Construction Progress Monitoring

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.

Adaptive smart shelter

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.

Unmanned Aerial System in Contact-based Inspection of Building Envelope

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.

Four-legged robot for remote progress monitoring

Legged robots are modern automation tools. Due to their flexibility and maneuverability, they are more suited for construction sites than other types of robots. This project evaluates the potential of using a four-legged robot for construction applications with a focus on progress monitoring and remote inspection.

Machine Learning for Facility Life Cycle Cost Analysis

Our team has been working on forecasting facilities' life-cycle cost (LCC) by implementing machine learning on historical data. We have proposed a comprehensive and generalizable framework for developing facility LCC analysis machine learning models. This framework specifies the data requirements, methods, and expected results in each step of the model development process.

Internet of Things in the Built Environment

With the networks of sophisticated sensors and devices, building systems have the potential to serve as the infrastructure that provides essential data for the Internet of Things (IoT)-enabled Smart Built Environment paradigm. However, current building systems lack inter-system connectivity or exposure to the larger networks of IoT devices. Our team is working on an IoT-enabled data acquisition framework that utilizes low-cost computers, sensors modules, developed software agents, and the existing building Wi-Fi network to establish a central facility database.

Building Data Interoperability

The objective of this project is to develop a systems interoperability that supports a network-based data exchange for collaboration in smart and connected design and construction process. We contribute to developing industry standards, system frameworks, and new automated solutions for seamless network-based data exchange in the process of design and construction.

Automated Inspection and Monitoring

Our projects include drone-based inspections and robotic inspection of buildings and infrastructures during construction through the operations. Our team has introduced a novel approach to automated inspection of buildings and infrastructure through the use of a six-legged robot. The proposed method will facilitate automated inspections during construction and operation while improving safety in workspace.