Sensor integration refers to the process of combining data from multiple sensors to provide a more comprehensive and accurate understanding of an environment or system. This often involves data fusion techniques to merge and correlate sensor readings, compensating for individual sensor limitations and improving overall reliability and performance. Common applications include robotics, environmental monitoring, industrial automation, and autonomous vehicles, where a combination of sensors like cameras, LiDAR, GPS, and IMUs are integrated to enable perception, navigation, and control.
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