The term data fusion in robotics is particularly at home in the fields of robotics, automation and artificial intelligence. Data fusion means that different sensors on a robot collate their information. This creates a more complete picture of the environment or situation than with just one sensor.
Imagine a robot working in a factory. For example, it has a camera and a laser sensor. The camera sees what colour an object is, the laser sensor measures the distance. On their own, both sensors only receive part of the information. However, if you combine both data sources - i.e. "merge" them - the robot recognises much more precisely where the object is and what it could 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 particularly indispensable for autonomous robots or self-driving vehicles in order to bring together the wealth of information from radar, cameras and other sensors in a meaningful way. This makes modern robots ever more efficient and safer to use.















