A hybrid sensing autonomous obstacle avoidance method and system for unmanned boats based on reinforcement learning

Abstract

The invention relates to a method and system for autonomous obstacle avoidance based on reinforcement learning based on hybrid perception of unmanned boats. The method includes the following steps: 1) building a marine environment; The provided global planning information and the obstacle information within the detection radius of the radar system are learned to obtain the reinforcement learning state code; 3) Set the reward target weight to obtain the comprehensive reward function; 4) Build and train the evaluation network and policy network; The learning state code is input to the evaluation network and the policy network respectively, the comprehensive reward function is input to the evaluation network, and the output of the controller is determined according to the action corresponding to the learned mean value of the policy network. Compared with the prior art, the present invention has a high self-learning ability, and can adapt to different large-scale complex environments through simple deployment and training, thereby realizing autonomous perception, autonomous navigation, and autonomous obstacle avoidance.

Description

technical field [0001] The invention relates to an autonomous obstacle avoidance method and system for an unmanned boat, in particular to a hybrid perception autonomous obstacle avoidance method and system for an unmanned boat based on reinforcement learning. Background technique [0002] Unmanned boat is a surface unmanned vehicle that can realize autonomous navigation, autonomous obstacle avoidance, and autonomous surface operations. It has the advantages of small size, high speed, good stealth and no risk of casualties. Unmanned boats are very suitable for performing surface operations tasks in dangerous sea areas with high risk of casualties or simple surface operations tasks that require low personnel participation. It has a good cost-effectiveness ratio, so it is widely and effectively used in marine monitoring. , marine survey, maritime search and rescue, unmanned cargo and other fields. [0003] At present, the mainstream idea of ​​realizing autonomous navigation of...

AI Technical Summary

Problems solved by technology

Although these methods have relatively good performance in their respective application backgrounds, they need to be carefully designed for different functional modules, and the comprehensive algorithm needs to be configured and adjusted as a whole, which makes the realization of the intelligent algorithm of the unmanned vehicle complex and cumbersome.

Furthermore, due to the lack of self-learning ability of these methods, it is difficult to adapt to large-scale and complex environments, and it is necessary to redesign, reorganize and cooperate with different algorithm modules for different environments.

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