University of Florida study: black-and-white stripe patterns can fool depth estimation in autonomous vehicles and robots

A University of Florida study found that simple black-and-white stripes or checkerboard patterns can cause errors in the stereo camera depth estimation of autonomous vehicles and robots, leading them to misjudge obstacle distances and even trigger sudden braking or collisions. The research team tested a variety of sensors, algorithms, and AI models and found that this fundamental vulnerability, which is based on repeating textures, is widespread, and that an attacker need only place a small-area pattern in a scene to affect depth computation; such patterns may also appear in natural environments.