Trolley real-time attitude detection method based on multi-sensor data fusion

The invention discloses a trolley real-time attitude detection method based on multi-sensor data fusion in the technical field of tunnel detection, which comprises the following steps of: (1) sampling real-time detection data of a current trolley through a three-axis accelerometer and a three-axis gyroscope; (2) filtering the real-time detection data by adopting a Kalman filter; (3) calculating the instantaneous state A and the distance B of the current trolley; (4) sampling and calculating, by the encoder, the motion distance C of the trolley; (5) calculating thethe current trolley posture by using data A, B and C as neural network input; (6) collecting, by the camera, an image and extracting a feature object contour; (7) calculating the real-time state D of the trolley according to the contour of the feature object; (8) according to the data of the D, recalculating the Kalman filter to obtain an updated value, and finely adjusting the output result of the step (5). The method can improve the detection preci