The term data fusion in robotics is primarily at home in the fields of robotics, automation, and artificial intelligence. Data fusion means that various sensors on a robot pool their information together. This creates a more complete picture of the environment or situation than would be possible with a single sensor.
Imagine a robot working in a factory. It has, for example, a camera and a laser sensor. The camera sees the colour of an object, and the laser sensor measures the distance. On their own, neither sensor provides a complete picture. However, by combining both data sources – in other words, „fusing“ them – the robot can more accurately identify where the object is and what it might be. This allows it to work more safely and efficiently.
Data fusion in robotics is used to make robots „smarter“: they navigate more reliably, avoid collisions, and make better decisions. Data fusion is indispensable, especially in autonomous robots or self-driving vehicles, to meaningfully combine the many pieces of information from radar, cameras, and other sensors. This makes modern robots increasingly powerful and safer in operation.
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