Israeli scientists use robotic arms and ancient water measurement techniques to accurately capture the 3D structure of complex objects.
The 3D scanning process can be tricky, especially if you're dealing with objects that contain cracks and other hidden parts. Researchers at the Ben Gurion University in Negev, Israel, are developing a technology that can eliminate the cumbersome problems typically associated with conventional 3D scanners .
The old method is that you can accurately measure the volume of an object by immersing it in water and analyzing the amount of water removed by the object.
Transform water and robots into 3D scanning solutions
A new scanning method called "impregnation conversion" works with the robotic arm and the bucket. The process begins by immersing the object in water and measuring its fluid displacement. Later, the researchers were able to construct a virtual 3D model using a mathematical algorithm that produced a series of "slices" of 3D in the form of objects.
According to the research team, this method has many advantages over other types of 3D scanning technology. Because there is no line of sight problem, unlike optical sensors, the robotic arm and aqueous solution capture hidden details within the object.
“Unlike optical sensors, liquids have no line of sight requirements. One of the authors, Andrei Sharf, says it penetrates the cavity and hidden parts of the object, bypassing all the visibility of traditional scanning equipment and Optical limitations.
Although this proof of concept is undoubtedly innovative, there are still some shortcomings in the scientist team. For beginners, the robot arm must currently move the selected object 500 to 1,000 times to create a high fidelity scan. This long wait for this process is a significant obstacle, but alleviating this problem will make the technology very useful.
By combining ancient Greek ideas with water and robots, researchers believe that their approach will allow people to correctly scan complex objects in more accurate ways than ever before.
However, it feels that this method is not only cumbersome, but also has a relatively large error.
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