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A Natural Language Control System for Application Specific Robots

by Yash Jajoo, Rutvij Supekar, Arrush Hegde
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 2
Year of Publication: 2017
Authors: Yash Jajoo, Rutvij Supekar, Arrush Hegde
10.5120/ijca2017915535

Yash Jajoo, Rutvij Supekar, Arrush Hegde . A Natural Language Control System for Application Specific Robots. International Journal of Computer Applications. 176, 2 ( Oct 2017), 18-21. DOI=10.5120/ijca2017915535

@article{ 10.5120/ijca2017915535,
author = { Yash Jajoo, Rutvij Supekar, Arrush Hegde },
title = { A Natural Language Control System for Application Specific Robots },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2017 },
volume = { 176 },
number = { 2 },
month = { Oct },
year = { 2017 },
issn = { 0975-8887 },
pages = { 18-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number2/28525-2017915535/ },
doi = { 10.5120/ijca2017915535 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:41:28.018740+05:30
%A Yash Jajoo
%A Rutvij Supekar
%A Arrush Hegde
%T A Natural Language Control System for Application Specific Robots
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 2
%P 18-21
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Due to the increasing presence of robots in several industries, human-robot interaction using natural language has become an important research area. The concept of controlling robots by transforming language instructions in English into executable code for robots is discussed. The proposed approach makes use of semantic similarity by comparing the given instruction with those within a corpus and executes the instruction most similar to the one given. The method is application specific but the modular nature of the system allows it to be adapted for any robot and for any purpose. For this project, a Raspberry Pi based robot following navigation commands is used for experiments and a success rate of 96% is observed.

References
  1. S. Tellex et al., "Understanding natural language commands for robotic navigation and mobile manipulation" in Proceedings of the National Conference on Artificial Intelligence (AAAI), Cambridge, MA, 2011.
  2. D. K. Misra et al., “ Tell me Dave: context sensitive grounding of natural language to manipulation instructions” in Proceedings of Robotics: Science and Systems, Berkeley, USA, July 2014
  3. L. She et al., "Back to the blocks world: Learning new actions through situated human robot dialogue" in Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), Philadelphia, PA, 2014, pp.89-97.
  4. C. Matuszek et al., "Learning to parse natural language commands to a robot control system" in Proceedings of International Symposium on Experimental Robotics, Quebec City, Canada, 2012.
  5. R.Rehurek and P.Sojka, "Software framework for topic modeling with large corpora" in Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, Valletta, Malta, 2010, pp.46-50
  6. T. Landauer, P. Foltz, and D. Laham, “An Introduction to Latent Semantic Analysis”, in Discourse Processes, Taylor and Francis, Nov 2009, pp.259-284
  7. RPi.GPIO 0.6.3. A module to control Raspberry Pi GPIO channels. https://pypi.python.org/pypi/RPi.GPIO
Index Terms

Computer Science
Information Sciences

Keywords

Human-Robot interaction NLP LSA semantic similarity.

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