METHOD FOR INFORMATION INTERACTION BETWEEN AN OPERATOR AND AN AUV EQUIPPED WITH A HYDROACOUSTIC COMMUNICATION CHANNEL FOR TARGET OBJECT IDENTIFICATION

Abstract

The execution of inspection and manipulation operations by autonomous unmanned underwater vehicles (AUVs) under operator supervision is limited by the low bandwidth of the hydroacoustic communication channel, which does not allow the transmission of video streams and high-quality photographic images in real time. At the same time, existing methods for automatic recognition of target objects by onboard machine vision systems of AUVs do not guarantee accurate determination of the object’s position and shape when defects are present on its surface (siltation, biofouling, mechanical damage). To address this problem, the paper formulates the task of developing a method that enables information interaction between the operator and the AUV via a low-bandwidth hydroacoustic communication channel. This interaction allows the operator to evaluate the quality of target object recognition and subsequently generate target designations for the vehicle and its onboard manipulator. The proposed method is based on an algorithm for identifying objects with defects, which employs a modified ICP point cloud registration approach with the exclusion of defective regions and characteristic features (CFs). The detected CFs and defect regions are transformed into a compact set of geometric primitives transmitted to the operator through the hydroacoustic communication channel with the AUV. Based on the received information, incoming telemetry from the AUV, and a reference three-dimensional model of the object, the graphical interface visualizes the scanned scene, allowing the operator to assess the recognition accuracy. Full-scale experimental tests of the method were conducted using a hydroacoustic modem manufactured by the Institute of Marine Technology Problems, Far Eastern Branch of the Russian Academy of Sciences (IMTP FEB RAS) and an onboard computer NVIDIA Jetson TX2. The information packet transmitted within 1 minute contained the object type, its position, a defect map, and the coordinates of the characteristic features, with a data volume three orders of magnitude smaller than that required for transmitting the full point cloud of the scanned object. Based on the received information, the operator confirmed successful object identification even when up to 30% of the surface area was covered by defects. The practical significance of the proposed method lies in enabling the execution of critical missions under operator supervision in conditions of environmental uncertainty