A target recognition method based on brain-like cross-media intelligence for unmanned autonomous system

Abstract

The invention provides a target recognition method based on brain-like cross-media intelligence for an unmanned autonomous system. The method comprises the following steps: 1. acquiring video and audio data of a target scene collected by an unmanned autonomous system, preprocessing the video and audio data, extracting language characters from the video and audio data, adopting distributed representation of the language characters, and obtaining a word vector; 2, combining that spatio-temporal context information of the object to carry out significant calculation on the preprocessed video-audiodata and the word vector; 3, training a multimodal fusion neural network according to that significance calculation result and the spatio-temporal context information of the object, and extracting attribute semantic information of the audio-visual data and the word vector; 4, according to that spatio-temporal context information of the object, the attribute semantic information and the prior knowledge of the target knowledge map, adopting cognitive calculation and Bayesian inference to obtain the target semantic information in the target scene. The invention can effectively improve the intelligent target recognition effect of the unmanned autonomous equipment.

Description

technical field [0001] The invention relates to the technical field of unmanned autonomous intelligent control, in particular to a target recognition method based on brain-like cross-media intelligence for unmanned autonomous systems. Background technique [0002] The integration of artificial intelligence and unmanned systems forms an unmanned autonomous system (UAS). At present, the unmanned autonomous system has formed an integrated system of land, sea, air and space. In mobile scenarios, the unmanned autonomous system is an important intelligent support system for intelligent robots and unmanned autonomous equipment to analyze and identify targets. [0003] The unmanned systems of intelligent robots (such as industrial robots, service robots, space robots, marine robots, and unmanned workshops, etc.) have successively experienced the development process of automation, intelligence, autonomy, and clustering. The system intelligent perception and control of unmanned auton...

AI Technical Summary

Problems solved by technology

At present, the target recognition of unmanned systems based on traditional methods, considering the complexity of the system and the difficulty of implementation, mostly adopts single-modal recognition methods, which cannot solve the problem of multi-modal differences in cross-media or cross-modal target attributes.

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