Sensor fusion combines data from multiple sensors into a shared and more robust environmental model.

Sensor fusion refers to combining data from multiple sensor modalities—typically camera, radar, lidar, ultrasound, or inertial sensors—into a shared environmental model. The major advantage is that the strengths of different sensors are combined and their weaknesses are partially compensated for, thereby increasing reliability, range, and accuracy. For data logging, sensor fusion is central because only precisely time-correlated and completely recorded sensor data enable robust offline analysis and validation of fusion algorithms.