GoKawiilVicOne LAB R7 shows manipulated sensor inputs can alter robot behavior
VicOne's LAB R7 research team tested how falsified or adversarial inputs—images, posters, and inaudible audio—can change robot behavior even when safety systems function as designed. In one test, text on a poster was misread as a command by a robot dog running Gemma 4 E4B, altering its movement; in another, crafted inaudible audio changed a simulated hospital robot's behavior using Nemotron on an NVIDIA Jetson AGX Orin. The team also cited published studies, including one on vision-language-action models and FreezeVLA, showing adversarial visual inputs can disrupt or override robot task execution.
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The findings suggest that robot safety mechanisms designed around correct sensor data may not account for scenarios where that data is deliberately falsified or corrupted, a gap that could matter as robots increasingly operate near people in hallways, factories, and hospitals. This indicates that securing robots may require treating environmental inputs as potentially untrustworthy, not just faulty, which could reshape how safety certifications and testing protocols are designed. VicOne's research implies that current safety assurances may be incomplete without considering adversarial manipulation as a distinct threat category.
- VicOne LAB R7 tested robots using Gemma 4 E4B and Nemotron models to study manipulated-input vulnerabilities.
- Poster text was misinterpreted as a command, altering a robot dog's movement in testing.
- Inaudible crafted audio changed a simulated hospital robot's behavior, separate from published studies on visual adversarial attacks.
Source: spectrum.ieee.org, 2026-10-27
Published there as: “Your Robot’s Safety Functions Already Work. What If the Input Lies?”
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