The invention discloses a real-time positioning method for a ground aircraft-winding inspection
robot, and the method comprises the steps: obtaining the wide-area
point cloud data of an aircraft, and building a stable coordinate
system with the aircraft as a reference through the recognition and registration of a plurality of semantic key points, such as a
nose cone and a wingtip, and a pre-stored template; the method comprises the following steps: acquiring
laser radar and camera data in real time, inputting the data into a pre-trained multi-
modal deep learning model, and outputting probability distribution representing the current
pose of a
robot under an aircraft coordinate
system by the model; in a filter, the mean value of the probability distribution is used as an observation value, the variance is used as dynamic observation
noise, optimal fusion with
motion prediction of the
robot itself is carried out, and a final smooth
pose is generated. According to the method, the real-time monitored
pose uncertainty is utilized, the robot is actively controlled to adjust the position so as to improve the sensing quality when the observation
view angle is poor, high-precision and high-robustness aircraft relative positioning is achieved, and the method has the
active sensing ability.