Q-learning based object grasping control strategy for home service robot with rotatable waist

Ya Fang Ho, Chien Feng Huang, Yi Lun Huang, Sheng Pi Huang, Hsiang Ting Chen, Ping Iiuan Kuo, Tzuu Hseng S. Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a Q-learning based object grasping strategy and control method is proposed for the home service robot with a rotatable waist. The home service robot May used in this study possesses 6-DOF arms, 2-DOF neck, a rotatable waist, the four-wheel independent steering and four-wheel independent drive mobile platform. In order to increase the coverage of grasping, this paper proposes the Q-learning controller to find the most suitable angle of waist for grasping the object By the grasping strategy, the position of end-effector is calibrated using an ultrasonic ranging module. Moreover, in order to avoid overload of servo motors, the home service robot May is able to utilize the other arm to assist when the object is really heavy. Finally, the experimental results demonstrate the feasibility and practicality of object grasping and control strategy.

Original languageEnglish
Title of host publicationProceedings of 2014 International Conference on Machine Learning and Cybernetics, ICMLC 2014
PublisherIEEE Computer Society
Pages714-720
Number of pages7
ISBN (Electronic)9781479942169
DOIs
Publication statusPublished - 2014 Jan 13
Event13th International Conference on Machine Learning and Cybernetics, ICMLC 2014 - Lanzhou, China
Duration: 2014 Jul 132014 Jul 16

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume2
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Other

Other13th International Conference on Machine Learning and Cybernetics, ICMLC 2014
CountryChina
CityLanzhou
Period14-07-1314-07-16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction

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  • Cite this

    Ho, Y. F., Huang, C. F., Huang, Y. L., Huang, S. P., Chen, H. T., Kuo, P. I., & Li, T. H. S. (2014). Q-learning based object grasping control strategy for home service robot with rotatable waist. In Proceedings of 2014 International Conference on Machine Learning and Cybernetics, ICMLC 2014 (pp. 714-720). [7009698] (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/ICMLC.2014.7009698