Reality capture has revolutionized construction by increasing job site efficiency and safety and allowing for quick responses to design and building challenges. However, save for the use of drones, often operated by humans, on-the-ground monitoring has required the relatively traditional (and labor-intensive) task of walking around and taking photos and collecting data to feed into software.
HoloBuilder, whose software helps builders document and analyze their underway projects, has partnered with the robotics firm Boston Dynamics to create a semi-autonomous solution to document under-construction projects. Using Boston Dynamics’ Spot, a dog-like robot that regularly goes semi-viral for its aerial acrobatics (and its more sinister uses, such as being put to work by the Massachusetts State Police), contractors can capture 360-degree overviews of their work and track changes throughout the build process.
Controlled by the SpotWalk app, the robot is first semi-manually trained to walk its reality capture route via a user’s phone. Then, Spot learns to repeat the route on its own, avoiding obstacles and documenting the site consistently and regularly, creating documentation of the project over time.
Contractor Hensel Phelps has been testing out Spot on the $1.2 billion San Francisco International Airport Terminal 1 project. A Spot unit walks through the site capturing imagery, which is then fed into HoloBuilder’s machine learning-powered SiteAI, which provides automated construction tracking and other data.
Documenting construction sites currently is a tedious task that takes away time from project staff that could otherwise focus on other aspects of construction, safety, and design. It can only be done with relatively limited regularity because of the demands. With Spot, project managers predict that they could capture updates of their sites as frequently as twice a day with all the 360 imagery being automatically organized and analyzed. Because of Spot’s greater consistency against humans, the photos are also more useful as tools and the collected data is more actionable due to its regularity.
