Environment-adaptive service strategy generation method for robot

被引：0
|
作者：
Tian G. [1 ]
Chen H. [1 ]
Zhang M. [1 ]
Cui Y. [1 ]
机构：
[1] School of Control Science and Engineering, Shandong University, Jinan
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2023年 / 51卷 / 02期
关键词：
deep learning; environmental-adaptive; keyword sequence; robotic service strategy; text generation;
D O I：
10.13245/j.hust.228784
中图分类号：
学科分类号：
摘要：
In order to improve the service task execution ability of robots in different home environments，an environment-adaptive service strategy generation method was proposed，which could generate the service strategy based on the current environmental goods information． Firstly，term frequency-inverse document frequency (TF-IDF) algorithm was used to construct service instruction set，keyword sequence set and service strategy data set．Secondly，semantic parsing and block analysis were carried out for irregular natural language instructions，which were decomposed and mapped to structured service instructions to simplify the semantic space and obtain the corresponding keyword sequence to be selected． Finally，the Protégé ontology knowledge base containing the current family environment information was matched and inferred to obtain the service keyword sequence，and the GPT-2 model fine-tuned by the service strategy data set was guided to generate the adaptive service strategy．Experimental results show that this method can improve the accuracy of service strategy generation，and the final generated strategy is more feasible in a specific family environment. © 2023 Huazhong University of Science and Technology. All rights reserved.
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页码：102 / 108
页数：6
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