Construction rework is not a mystery to anyone who has spent time on a job site, but the scale of it still catches people off guard. The Construction Industry Institute puts it at more than 10 percent of total construction costs. Other estimates put the annual toll upwards of $100 billion.
Those numbers were the starting point for a recent webinar hosted on Commercial UAV News entitled Autonomous Mapping Robots Can Reduce Construction Rework, which was sponsored by Exyn Technologies. Matt Malencia, senior technical project manager at Exyn, and Kenneth Fronheiser, director of strategic integration and technology at Keystone Precision Solutions, spent the hour-long session walking through why rework happens, where traditional survey tools fit, and how autonomous SLAM-based mapping is starting to close some of the gaps.
Read below for a recap of some of the topics discussed during the conversation, and click the button for your free registration, which provides an on-demand recording of the full webinar.
Fronheiser opened with a rundown of the tools already in most surveyors' toolboxes: total stations, terrestrial laser scanners (TLS), and GNSS. Each has a place. Total stations are built for individual, high-accuracy point measurements. TLS units capture dense point clouds well suited to facade scans, tank inspections, or renovation work. GNSS struggles under bridges, in urban canyons, or under tree cover, and total stations need a clear line of sight to a backsight, which gets harder on congested sites.
Those limitations, combined with incomplete site data, inaccurate bid packages, late design changes, and plain human error, are the four causes of rework to which the discussion kept returning. Fronheiser added a fifth pressure sitting underneath all of it: a shrinking, aging workforce in the surveying industry. He noted that the average licensed surveyor is in his or her mid-to-late 50s, with too few people moving up to replace them. Smaller teams doing the same amount of work means less frequent scanning, which in turn means more outdated data feeding into decisions.
Fronheiser shared an example in which identical rooms at a research facility needed the same renovation. One was laser scanned before work began. The other was hand-measured. The hand-measured room resulted in 13 to 15 change orders, while the scanned room had one. The scanned project also finished ahead of schedule and under budget. As Fronheiser put it, a little more time upfront can prevent a lot of pain downstream.
Malencia used that setup to introduce SLAM, or simultaneous localization and mapping, the technology behind both handheld mobile scanners and autonomous mapping robots, including drones. SLAM answers two questions at once: what is around the device, and where is the device relative to it. Unlike a stationary TLS unit, a SLAM scanner is moving through the environment, so it has to continuously correct for drift as it builds its map.
The same SLAM engine that runs Exyn's modular Nexys scanner also powers its autonomous drone platform without a pilot. Malencia framed autonomy not as a replacement for survey-grade tools but rather as an expansion of what is practical to scan often. Traditional TLS and total stations still own the high-accuracy, low-frequency end of the spectrum, things like survey control and final QA. Autonomous SLAM opens up the high-frequency side, where speed and repeatability matter more than shaving off the last few millimeters, like routine progress monitoring or as-built-to-plan checks.
The clearest proof point came from a U.S. Army Corps of Engineers project mapping a complex urban structure. A single autonomous flight with Exyn's system captured the space in about four minutes, while a traditional tripod-based approach took more than 30 setups and over an hour and a half. That gap is what makes frequent, low-disruption scanning realistic even on active, complex sites, including overnight or during shift changes with no crew on site at all.
Malencia's closing point was less about accuracy and more about mindset. Instead of chasing millimeters, he argued, teams should think about how much value there is in simply knowing what changed on site since yesterday. Catching a change or a mistake early stops the cascading errors that lead to expensive rework later.
The full session includes a deeper look at the Exyn Nexys hardware, Exyn’s levels of aerial autonomy, and audience questions on topics like photogrammetry versus SLAM, licensing, and how to decide which method fits which part of a project. Register for the on-demand recording to watch it in full.
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