The Method of Intelligent Mission Planning for Autonomous Underwater Vehicles

Creation of fully autonomous unmanned underwater vehicles and systems capable of performing various research and technological operations under uncertainty conditions is a pressing issue. The key problem is automatic mission correction in real time based on data from onboard systems. The aim of this work is to develop a method for intelligent mission planning at the strategic control level of autonomous underwater robotic systems, enabling automatic generation of adaptive plans and their transformation into tactical-level executable commands for operation in changing environmental conditions. In the article, the authors define the principles of developing an intelligent mission planner for autonomous underwater robotic systems (AURS) at the strategic level and a mission manager for managing the mission at the tactical level with the formation of specific tasks for performers. A formal model for planning missions through many linear sections with preconditions and postconditions has been developed. The key aspect of the proposed solution is the use of an ontological approach to standardize the description of missions and ensure their software interpretation. A specialized mission development environment has been created on the IACPaaS cloud platform, allowing experts to form and adapt mission plans without delving into technical details. The set of tools with a modular architecture has been developed, ensuring scalability and adaptation of the solution for various classes of submarines and types of missions. The results of testing have shown that the proposed solution allows for the formation of flexible plans that take into account the diversity of situations and automatically select command sequences depending on the incoming data. The results obtained open up new possibilities for creating fully autonomous underwater systems capable of performing complex research and technological operations without constant operator control. Further research is aimed at improving the mission manager algorithms, as well as integrating the planner with other onboard support components.