Australian ‘Stabbing Machine’ Robot Helps Study Knife Crimes

An Australian robot known as the “stabbing machine” is helping forensic experts to study the different factors and variables of violent knife crime.

“When a person gets stabbed, rips in the victim’s clothing may contain clues to help catch the attacker,” explained Popular Science last week. “Forensic scientists are trying to understand what tears and distortions in the fabric around a stab wound can say about the knife type, angle of attack, and stabbing technique that caused the wound.”

The machine boasts an “interchangeable knife holder,” “simulation of stab events through pneumatic system,” “60 stabbing positions via an Arduino microcontroller and knife holder,” and a “robust and highly reproducible positioning system,” allowing the robot to recreate various knife crime scenarios that feature different knives and variables with more accuracy and precision than a human.

“Various types of knives make various types of cuts, as you might expect, and the shapes of holes left in clothes can indicate whether the weapon was serrated, dull, curved and so on,” wrote Tech Crunch. “Ordinarily a human stabber is employed in recreating these holes in test fabric — for comparison, you understand — but people are notoriously un-robotic in their execution of this type of task, and, as in other things, small deviations in force and angle creep in where unvarying exactitude is needed.”

Despite the potential benefits, Popular Science reports that the machine still needs to improve greatly, as it currently only “jabs” at the force of a human bite.

“Future versions of the machine will probably need to work on accuracy, consistency, and power—the device currently jabs at a pressure of 1 megapascal, which is about the force of a human bite,” they declared. “But eventually, a device like this could help to turn the analysis of textile damage into a science.”

Charlie Nash is a reporter for Breitbart Tech. You can follow him on Twitter @MrNashington or like his page at Facebook.

 


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