Simulation Engines Cross into Embodied AI: An Anti-Fraud Engineer's View on 'Black Market-Level' Challenges

At the WAIC 2026 exhibition hall, I stood in front of Lingshu Technology's booth, watching them use a garment simulation engine to drive a robotic arm to grab fabric. An engineer from a neighboring exhibitor muttered quietly: "The physics of this fabric feels just like the real thing, but the robotic arm's grasping success rate is only 68%." My brain immediately jumped to a typical anti-fraud scenario: When there is a deviation of more than 5% between simulation data and the real environment, the model will generate systematic false positives online. From garment simulation to embodied intelligence, this crossover isn't just simple technology transfer; it's solving a problem of "data credibility," which happens to be exactly what I do daily.