What is sensor fusion?

Sensor fusion is the process of combining data from multiple different sensors—such as LiDAR, stereo cameras, radar, ultrasonic sensors, GPS, and inertial measurement units (IMUs)—to create a more accurate, reliable, and comprehensive understanding of an autonomous mobile robot’s environment and operational state. By integrating diverse sensor inputs, sensor fusion mitigates the limitations and noise of individual sensors, enabling the robot to perceive and interpret its surroundings with higher precision.

Why is sensor fusion important?

In autonomous mobile robots, sensor fusion is essential for robust navigation, real-time obstacle detection and avoidance, precise localization, mapping, and overall safe operation, especially in complex or changing environments. For example, cameras provide rich visual information but may struggle in poor lighting or foggy conditions, whereas LiDAR excels at precise distance measurement regardless of lighting; sensor fusion intelligently merges such data to maintain continuous, reliable situational awareness.