Geo Week News

April 6, 2020

Is mm level accuracy not important anymore?

Green dart in target

In the past few years the reality capture industry has seen an explosion of new solutions entering the market. Many of these solutions are not following the typical aspirations we have seen traditionally from new products entering the market. Until recently, many of the new products entering the market were chasing one of two goals, accuracy and/or range. A few years back accuracy and the gold standard of millimeter or even sub-millimeter accuracy were the goals for new product development if not aiming to achieve this accuracy at increased ranges or others purely aiming at increased range.

But now, it is not unusual to see solutions chasing 5 mm level accuracy or scan setup times in under a minute or having no setup times at all and going mobile. In fact, rarely does mm accuracy get the spotlight anymore. Is mm level accuracy not important anymore? Does accuracy hold a place in our tool belts anymore? Or are the needs of the reality capture market changing or expanding to include needs that do not rest solely on accuracy?  In today’s reality capture environment we now have a multitude of solutions that are not aiming for purely accuracy, but much more.

Solutions entering the market in today’s climate tout more than the statistic of accuracy. Now we see new parameters being touted such as speed of a scan setup time, scan registration automation, scanning without the need for setups, point density of the solution, and more. The market used to rely entirely on increasing the accuracy  of the solution and with this expansion of variables that must now be considered, we are developing what has been characterized as a reality capture spectrum. We have a range of available solutions that vary not only in accuracy, but also speed, point density, coverage, and more even looking further downstream of workflows that ensure expedited registration time. The once simple question of what solution do I need for a project, now has become complex and exhaustive.

The conundrum of speed

So besides accuracy, what else are companies bringing to market to help solve interesting problems? To start, one of the biggest issues facing the traditional market was speed. Oftentimes scans could offer great accuracy but with great sacrifice to speed and time on site. When you enter a project that has time constraints for clients or production needs, time is of the essence. And when time and speed of capture may get in the way, you begin to think of how to make the project successful and what is the bare minimum needed for success. Oftentimes, one of the first things to go is colorization of the data.

To some, colorization may seem like a luxury, but regardless of opinion, scan time can double if not triple when adding color to scans. Color can be a huge benefit when generating context for a project or the team to understand the project. Along with long scan time, the more complex a project is and the more setups required to capture enough coverage of an area of interest, the more difficult it will be to capture quickly. So with speed being a major issue of capture, it is no secret the market is looking for solutions that can reduce scan time to a couple minutes if not less than a minute a scan. With this increase in speed comes a reduction in accuracy and the nuances of the reality capture spectrum begin.

Speed is a larger issue than previously thought seeing as how many solutions are aiming at faster setup time as well as looking past setup time to another breed of reality capture solutions. Mobile solutions have expanded as well within the market, but they are not new. Mobile scanning has been around for some time, but what has changed as of recently is the scale of which is looking to be captured. Many clients and owners are seeing reality capture documentation as the new as-builts for existing conditions as well as the construction sector has seen an increased use for this data. However, it is difficult to use traditional mobile lidar systems under these project needs and similarly, the marathon of static scan setups needed to capture the proper amount of coverage on an active construction site would be enough to persuade anyone from diving into this industry. This is where handheld scanning has gained traction.

Managing density

Handheld mobile scanning can now offer the proper amount of coverage needed to properly map an active site or begin generating existing conditions in record time for facilities with out of date or no documentation. What these mobile devices offer is coverage  and potentially increased density of data. These devices allow immense amounts of data to be captured continuously in real time utilizing a number of different integrations for capturing many more vantage points of the area of interest. This variable can be incredibly important for difficult to reach spaces or time constrained sites where to capture with a static scanner would not be possible. To give an example of coverage, we can use a typical pipe cross section. For static scanning from one vantage point towards a pipe, it may capture approximately 25% of the full diameter of the pipe. With a handheld mobile scanner and the ability to walk around the pipe at many different vantage points, it may capture approximately 75% of that same pipe. This comes with the concept that the more vantage points towards an object or area, the better coverage that can be achieved. The advantages here may be an increased ability for feature extraction, but like earlier, there are always trade offs. With mobile systems of course, the system is moving while scanning and this movement must be taken into account and balanced to ensure the data being captured is accurate to within a standard. So while you may have more coverage, you have less accuracy.

A similar concept to coverage is the idea of density. An easy example of varying densities on reality capture solutions can be seen when comparing aerial LiDAR to static scanning. Aerial LiDAR solutions aim at a few points per square meter, whereas static scanning solutions rarely communicate in these terms. Instead they may talk in ways of how many points they can capture per second, whether that is in the thousands or in the millions. Additionally, other LiDAR solutions tout how many lines they scan with as well as what sort of field of view. This mimics the idea of a level of accuracy or detail where we can think of a square meter example that an aerial LiDAR system would capture a few points versus a static scanner capturing somewhere in the thousands. This concept is similar to coverage, but coverage can be seen as the ability to capture more vantage points of a 3D environment whereas density can be seen as the distance between data points captured.

Considering the whole workflow

Many more considerations must be made when selecting a solution for a project including the entire workflow in getting from initial capture to the answer needed and the decision is enough to give anyone new or seasoned paralysis by analysis. What is clear however is that the industry is evolving and taking a closer look past accuracy and into the needs of the problems they are trying to solve. This idea of millimeter level accuracy for everything appears to be enough accuracy for many, but as more solutions enter the market, many more are reconsidering this idea of their “minimum effective dose of accuracy.” The goal is still to achieve accurate measurements and data points, but what is changing is the acceptable tolerance or estimated error around those measurements.

So with that what solution is the best on the market? Is it the fastest scanner out there? Is it the longest range scanner? Or is it still the gold standard of millimeter/sub-millimeter accuracy? What this expansion in the market is forcing professionals and clients to consider is not what’s the most accurate scanner out there, but instead what are the specific needs of my project. With all the variables in the equation now, it is vital to understand where your needs lie within the reality capture spectrum.

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