Shanghai University

Xiangfeng Luo

Shaorong Xie

Hang Yu

The present disclosure relates to the technical field of decision-making of unmanned surface vehicles, and provides a brain-like memory-based environment perception and decision-making method and system for an unmanned surface vehicle. The method includes: obtaining an image of an environment in front of an unmanned surface vehicle; and inputting the image of the environment into an environment perception and decision-making model of the unmanned surface vehicle, and outputting an action instruction, where the environment perception and decision-making model of the unmanned surface vehicle includes an image feature extractor, a Bidirectional Encoder Representations from Transformers (BERT) model, a fully connected layer, a short-term scene memory module, and a long-term memory module that are connected in turn; the BERT model extracts an image feature representation containing a text feature from an image feature. The present disclosure improves accuracy of decision-making of an action.

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Shanghai, China

Xiangfeng Luo