Example Concept: Sensor data integration in robotics often employs sensor fusion techniques such as Kalman filtering or complementary filtering to combine data from multiple sensors. These methods help in reducing noise, compensating for individual sensor weaknesses, and providing a more reliable estimate of the robot's state. Real-time constraints require efficient algorithms to process data quickly, ensuring that control systems can react promptly to changes in the environment.