Autonomous collision avoidance decision-making method for unmanned ship based on adaptive navigation situation learning

Abstract

The invention discloses an autonomous collision avoidance decision-making method for an unmanned ship based on adaptive navigation situation learning. The autonomous collision avoidance decision-making method comprises the steps that firstly, navigation state information of the unmanned ship is analyzed and described, and a navigation situation estimation body concept model of entity class and seaarea attribute in the navigation environment is established; secondly, a relation between the unmanned ship and an obstacle is determined as a binary relation, the body model is quantitatively divided into various navigation situation sub-scenes by combining with the international maritime collision avoidance rule; and thirdly, the current environmental state information of the unmanned ship in the sub-scenes is obtained, a feedback memory unit of a long-short term memory network is constructed, a ship autonomous collision avoidance decision-making algorithm is utilized to interact with the marine environment, and the optimal strategy of autonomous collision avoidance is calculated through adaptive navigation situation learning. According to the autonomous collision avoidance decision-making method, dimensionality reduction is conducted on the navigation situation of collision avoidance decision-making adaptive learning, thus the feasibility of decision-making is greatly improved, theiterative speed of the algorithm is greatly increased, and real-time autonomous obstacle avoidance and navigation safety of the unmanned cargo ship are ensured.

Description

Technical field [0001] The present invention relates to the field of unmanned ship control, in particular to an autonomous collision avoidance decision method for unmanned ships based on adaptive navigation situation learning. Background technique [0002] At this stage, there are few researches on autonomous collision avoidance decision-making of unmanned ships at home and abroad, and most of them have some achievements in the fields of unmanned boats and unmanned vehicles. The application methods are based on ship collision avoidance decision-making system, knowledge base, expert system, fuzzy Logic, neural network, evolutionary computing, swarm intelligence, immune algorithm and other methods, but these methods usually need to assume complete environmental information, but for uncertain environments, it is difficult to form a complete knowledge base, which is required in a large number of interactions with the environment Unmanned ships have strong self-adaptive capabilities, ...

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Problems solved by technology

[0002] At this stage, there are few researches on autonomous collision avoidance decision-making of unmanned ships at home and abroad, and most of them have made some achievements in the fields of unmanned boats and unmanned vehicles. Logic, neural network, evolutionary computing, swarm intelligence and immune algorithm, etc., but these methods usually need to assume complete environmental information. However, for uncertain environments, it is difficult to form a complete knowledge base. In a large number of interactions with the environment, it is necessary to Unmanned ships have strong self-adaption capabilities, and use sensors to perceive obstacle information in real time for online decision-making and collision avoidance

For unmanned transport cargo ships, there are few researches on autonomous collision avoidance decision-making, and the application is not skilled, and it still faces the problem of autonomous navigation of ships and autonomous decision-making of collision avoidance of ships in complex waters.

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