Information Processing Model of Machine Maps

被引：0
作者：
You X. [1 ]
Li K. [1 ]
Tian J. [1 ]
Yang J. [1 ]
Yu A. [1 ]
Jia F. [1 ]
机构：
[1] School of Geospatial Information, Information Engineering University, Zhengzhou
来源：
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2024年 / 49卷 / 04期
关键词：
continuous autonomous learning; information processing model; integrated sensing mapping and decision-making capacities; machine maps;
D O I：
10.13203/j.whugis20230319
中图分类号：
学科分类号：
摘要：
Objectives: The autonomous cognitive ability of unmanned platforms to complex environments is a key issue restricting their extensive real-world application, and has become a research hotspot in cognitive science, artificial intelligence, cartography and other fields. From the perspective of complementary advantages of human-machine, the machine maps information processing model is proposed to achieve the logical expressions of machine maps information storage, processing, interaction and learning based on the conceptual model and cognitive characteristics of machine maps. Methods: An environmental representation model including perception map, working map and long-term map is constructed, and the map structure is analyzed from the perspective of observation angel, reference frame, information abstraction degree, data structure and description precision. An integrated information exchange pattern for measurement, production and application is established, including environment perception, mapping, work and decision-making, and meanwhile the continuous iterative environmental information processing process of this model is analyzed. A continuous autonomous learning model is also established, and the characteristics of the model in terms of learning process, learning content and persistence mechanism are analyzed. Results: Two experiments are carried out to verify the feasibility of the information processing model. The first experiment improves the long-distance autonomous navigation capability of the benchmark model by simulating the integrated sensing, mapping and decision-making capacities. The second experiment enhances the correlation between environmental factors and tasks by simulating the task driven process of creating working map, thereby improving the efficiency of task decision-making. Conclusions: The proposed model is able to provide a theoretical basis for the establishment of machine maps technology structure and system architecture, which in turn guides the development of machine maps system application. © 2024 Editorial Department of Geomatics and Information Science of Wuhan University. All rights reserved.
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页码：516 / 526
页数：10
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