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FICS Researchers finds simple visual patterns can trick AI-powered vehicles and robots

Dr Rampazzi and other researchers experimenting on Stereo-Vision-Vulnerabilities

A simple pattern of black-and-white stripes could cause an autonomous vehicle or robot to misjudge how far away an obstacle is, potentially triggering an unexpected maneuver or even a collision, according to FICS Research.

These things can also happen naturally, so it’s not a matter of imagining a sophisticated attacker. It becomes a safety problem,” said Dr. Sara Rampazzi, lead of the research effort.

Repeated visual patterns, like stripes on a fence or other regularly spaced objects, can cause the systems to incorrectly calculate depth.

Dr. Rampazzi’s team, two universities in Japan, tested multiple sensors, algorithms and AI models and found the same fundamental vulnerability across them, suggesting the problem is not limited to a particular manufacturer or application.

For traditional depth-estimation algorithms, the researchers developed a software-based change that can recognize situations involving repeated patterns and prevent the system from selecting an incorrect depth calculation. For AI-based systems, they modified the models, so they can respond differently when those patterns appear.

Read the Research here!
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