Fluid loading and unloading arm dynamic high-precision docking control method and system in unstable environment based on imitation learning

Abstract

The application discloses a dynamic high-precision docking control method and system for a fluid loading and unloading arm in a non-steady environment based on imitation learning, and the method comprises the following steps: initializing the end position of the fluid loading and unloading arm to a position at which complete image information can be collected; collecting a ship receiving device marker point image in real time, and calculating a visual feature error vector; inputting the visual feature error vector into a Gaussian mixture model regression model which is trained in advance by using an expert demonstration data set, and outputting a dynamic compensation speed vector; calculating a control instruction for minimizing docking deviation according to the visual feature error and the compensation speed; and driving a hydraulic execution system of the fluid loading and unloading arm to perform real-time adjustment according to the control instruction until the visual error converges, and high-precision docking of the end of the fluid loading and unloading arm and the ship receiving device is completed. The application is suitable for cm-level accurate docking of a fluid loading and unloading arm in a non-steady marine environment coupled by strong wind and sea waves, and significantly improves the safety and reliability of dangerous fluid conveying operations.

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