Commanding Mobile Robot Movement based on Natural Language Processing with RNN Encoder-Decoder

被引：0

作者：

Kahuttanaseth, Wittawin ^{[1
]}

Dressler, Alexander ^{[1
]}

Netramai, Chayakorn ^{[1
]}

机构：

[1] King Mongkuts Univ Technol North Bangkok, Software Syst Engn, Sirindhorn Int Thai German Grad Sch Engn, Bangkok, Thailand

来源：

PROCEEDINGS OF 2018 5TH INTERNATIONAL CONFERENCE ON BUSINESS AND INDUSTRIAL RESEARCH (ICBIR): SMART TECHNOLOGY FOR NEXT GENERATION OF INFORMATION, ENGINEERING, BUSINESS AND SOCIAL SCIENCE | 2018年

关键词：

component; Natural Language Processing; Machine Learning; Autonomous Mobile Robot; RNN Encoder-Decoder;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This work utilizes the potential of NLP and machine learning for the challenging task of human-machine communication. A task of robot movement is selected as the context of the research work where the goal is to create a software system that receives natural language input movement command from human and produces the set of precise trajectory information for the robot to perform. The proposed system consists of Pre-processing function, Command classification, Parameter classification, Post-processing function where RNN Encoder-Decoder is used for the implementation of the classification process. The system was trained using a dataset of 1,600 unique entries. The experiment results show that the average accuracy in case of single movement command is 79.23% whereas the average accuracy in case of multiple command in one sentence is 73.65%

引用

页码：161 / 166

页数：6

共 50 条

[1] Translation of Natural Language Query Into Keyword Query Using a RNN Encoder-Decoder
Song, Hyun-Je
Kim, A-Yeong
Park, Seong-Bae
[J]. SIGIR'17: PROCEEDINGS OF THE 40TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, 2017, : 965 - 968
[2] Neural-based Natural Language Generation in Dialogue using RNN Encoder-Decoder with Semantic Aggregation
Van-Khanh Tran
Le-Minh Nguyen
Tojo, Satoshi
[J]. 18TH ANNUAL MEETING OF THE SPECIAL INTEREST GROUP ON DISCOURSE AND DIALOGUE (SIGDIAL 2017), 2017, : 231 - 240
[3] Generating Chinese Classical Poems with RNN Encoder-Decoder
Yi, Xiaoyuan
Li, Ruoyu
Sun, Maosong
[J]. CHINESE COMPUTATIONAL LINGUISTICS AND NATURAL LANGUAGE PROCESSING BASED ON NATURALLY ANNOTATED BIG DATA, CCL 2017, 2017, 10565 : 211 - 223
[4] An Encoder-Decoder Framework Translating Natural Language to Database Queries
Cai, Ruichu
Xu, Boyan
Zhang, Zhenjie
Yang, Xiaoyan
Li, Zijian
Liang, Zhihao
[J]. PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 3977 - 3983
[5] RNN Encoder-Decoder for the inference of regular human mobility patterns
Katranji, Mehdi
Sanmarty, Guilhem
Moalic, Laurent
Kraiem, Sami
Caminada, Alexandre
Selem, Fouad Hadj
[J]. 2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2018,
[6] Mining Implicit Intention Using Attention-Based RNN Encoder-Decoder Model
Li, ChenXing
Du, YaJun
Wang, SiDa
[J]. INTELLIGENT COMPUTING METHODOLOGIES, ICIC 2017, PT III, 2017, 10363 : 413 - 424
[7] Software reliability prediction using a deep learning model based on the RNN encoder-decoder
Wang, Jinyong
Zhang, Ce
[J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2018, 170 : 73 - 82
[8] Natural Scene Text Recognition Based on Encoder-Decoder Framework
Zuo, Ling-Qun
Sun, Hong-Mei
Mao, Qi-Chao
Qi, Rong
Jia, Rui-Sheng
[J]. IEEE ACCESS, 2019, 7 : 62616 - 62623
[9] Prediction of Pedestrian Trajectory in a Crowded Environment Using RNN Encoder-Decoder
Xiong Xincheng
Bhujel, Niraj
Teoh, Eam Khwang
Yau, Wei-Yun
[J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON ROBOTICS AND ARTIFICIAL INTELLIGENCE, ICRAI 2019, 2019, : 64 - 69
[10] Pedestrian Trajectory Prediction Using RNN Encoder-Decoder with SpatioTemporal Attentions
Bhujel, Niraj
Yau, Wei-Yun
Teoh, Eam Khwang
[J]. 2019 IEEE 5TH INTERNATIONAL CONFERENCE ON MECHATRONICS SYSTEM AND ROBOTS (ICMSR 2019), 2019, : 110 - 114

← 1 2 3 4 5 →