Complete the sentence to define sensor fusion.
Sensor fusion is the process of combining data from multiple [1] to improve accuracy.
Sensor fusion combines data from multiple sensors to get better information than from one sensor alone.
Complete the sentence to explain why sensor fusion is useful.
Sensor fusion helps to reduce [1] by combining data from different sources.
Sensor fusion reduces noise, which means errors or random variations in sensor data, by combining multiple measurements.
Fix the error in the sentence about sensor fusion methods.
Common sensor fusion methods include Kalman filter, Bayesian [1], and neural networks.
The correct term is Bayesian estimation, which is a statistical method to estimate true values from noisy data.
Fill both blanks to complete the sensor fusion formula.
The fused estimate is calculated as: estimate = [1] * sensor1 + [2] * sensor2
The formula uses weight1 and weight2 to combine sensor1 and sensor2 data proportionally.
Fill all three blanks to complete the sensor fusion condition.
if sensor1 [1] sensor2 and confidence1 [2] confidence2 then fused = [3]
The condition checks if sensor1 value is greater than sensor2, and if confidence1 is less than confidence2, then the fused result uses sensor2.