Multisensor systems combine data from multiple types of sensors (like camera, LiDAR, radar, GPS, IMU) to provide a comprehensive and accurate understanding of an environment—especially in AI and robotics applications.
🔹 Key Features:
- Fuses data from different sensors to improve perception, accuracy, and robustness.
- Handles complex scenarios where a single sensor may fail (e.g., poor lighting, weather).
- Enables 3D spatial understanding and object tracking.
🔹 Common Sensors Used:
- Cameras – visual information
- LiDAR – 3D depth and distance
- Radar – velocity and distance, good in poor visibility
- IMU – motion/orientation data
- GPS – location coordinates
🔹 Use Cases:
AR/VR systems: Spatial awareness for immersive user experience.
Autonomous vehicles (ADAS): Combine camera + LiDAR + radar for real-time decision-making.
Drones: Navigation and obstacle avoidance using GPS + IMU + visual sensors.
Robotics: Enhanced object detection and localization in industrial or healthcare robots.