Ship intelligent collision avoidance method based on reinforcement learning

A technology of reinforcement learning and collision avoidance, applied in collision avoidance and other directions, can solve the problems of collision avoidance strategy not being able to learn and improve by itself, instability, etc., to reduce misoperation and improve efficiency.

Active Publication Date: 2018-11-16
WUHAN UNIV OF TECH
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Problems solved by technology

[0002] In the process of navigation, ship collision avoidance is a problem that cannot be ignored. There are many different solutions to this problem, using intelligent decision-making for ship collision avoidance based on AIS, using intelligent algorithms for ship collision avoidance based on evolutionary genetic algorithms, and based on Bayesian networks The ship collision avoidance algorithm, etc. These algorithms have a certain ability to solve the ship collision avoidance problem, but they also have their limitations, they cannot self-learn and improve the collision avoidance strategy
[0003] At present, the problem of ship avoidance

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Embodiment Construction

[0014] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0015] In the field of machine learning, reinforcement learning is an artificial intelligence method. The research team represented by the DeepMind team first proposed a deep reinforcement learning method based on DQN (Deep Q-Network), and used some Atari2600 games as test objects. The results can exceed Human players, the effect is remarkable. In 2012, Lange further started to apply and proposed Deep Fitted Q learning for vehicle control. The test shows that this method is applicable to the fields of intelligent control, robotics and analysis, prediction, e...

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Abstract

The invention discloses a ship intelligent collision avoidance method based on reinforcement learning. The ship intelligent collision avoidance method based on reinforcement learning comprises the steps of firstly, obtaining static data and dynamic data of two ships; secondly, checking the validity of the data and judging whether a collision avoidance program needs to be started or not; calculating a relevant collision avoidance parameter and judging whether a dangerous situation can be caused or not; if the collision danger cannot be generated, enabling the ships to advance by keeping speedsand directions according to a collision avoidance rule; if the collision danger can be generated, using a reinforcement learning method to learn a collision avoidance strategy, using input data as thecalculated parameter to perform training, outputting a strategy generated after training and obtaining a rudder angle for which the ship needs to steer; thirdly, executing the strategy, dynamically updating the dynamic data of the two ships in the step 1 and returning a bonus value; and fourthly, determining a reversion time of course according to the collision avoidance rule after the executionof the strategy is finished, and then enabling the ship to reverse the course. According to the ship intelligent collision avoidance method based on reinforcement learning, autonomic learning and improvement of ship collision avoidance are realized, and an unfavorable situation caused by sailors and so on absolutely relying on experiences is avoided.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and relates to an intelligent collision avoidance method for ships, in particular to an intelligent collision avoidance method for ships based on reinforcement learning. Background technique [0002] In the process of navigation, ship collision avoidance is a problem that cannot be ignored. There are many different solutions to this problem, using intelligent decision-making for ship collision avoidance based on AIS, using intelligent algorithms for ship collision avoidance based on evolutionary genetic algorithms, and based on Bayesian networks These algorithms have a certain ability to solve the problem of ship collision avoidance, but they also have their limitations. They cannot self-learn and improve the collision avoidance strategy. [0003] At present, the problem of ship avoidance in open waters involves multiple ships. The existing methods of ship collision avoidance in op...

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Application Information

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IPC IPC(8): B63B43/18
CPCB63B43/18
Inventor 张蕊王潇刘克中吴晓烈刘炯炯
Owner WUHAN UNIV OF TECH
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