No single sensor gives a robot a complete, reliable picture of its environment, which is why sensor fusion, combining data from multiple sensor types, is a core, unglamorous part of how physical AI actually works.
Cameras struggle in poor lighting and can’t directly measure distance precisely. Force sensors detect contact but reveal nothing about what’s approaching before contact happens. Each sensor type has real, specific blind spots that another can often cover.
Rather than trusting any single sensor’s reading in isolation, a fusion system combines multiple sensor streams, visual, force, inertial, sometimes tactile, weighing each based on known reliability in the current situation, producing a more accurate and robust understanding than any single sensor alone.
Our explainer on humanoid robot design covers why balance is one of the hardest unsolved problems: it depends on fusing inertial data with force feedback many times per second, a direct, continuous application of sensor fusion under real time pressure.
Foundational, if unglamorous, part of how physical AI systems build a reliable picture of their environment. See NVIDIA’s own Cosmos platform page for more.
