NDLI: Implementation of human following mission by using fuzzy head motion control and Q-learning wheel motion control for home service robot

Content Provider	IEEE Xplore Digital Library
Author	Ri-Wei Deng Yin-Hao Wang Chih-Jui Lin Li, T.-H.S.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan (Ri-Wei Deng; Yin-Hao Wang; Chih-Jui Lin; Li, T.-H.S.)
Abstract	This paper mainly implements human following function for home service robot, May, developed in our laboratory. In order to follow the operator accurately, visual tracking is composed by Tracing-Learning-Detection (TLD) and Kinect skeleton, where TLD plays the role as re-detecting the situation that operator is occluded or disappeared, and Kinect skeleton is adopted to track all other situations while TLD is learning how to enlarge operator image patterns in order to enhance recognition rates. For the sake of improving tracking capability, fuzzy head motion control is added in the visual tracking system to compensate the constraints that the mobile platform of May cannot react rapidly. Every instant movement of the operator can be captured by fuzzy head motion control in real time. Q-learning is applied to discover the pose switching of the mobile platform such that May possesses more robust following ability. By Q-learning, states setting are based on three dimensional position, actions are created by the pose of four wheel independent steering and four wheel independent driven (4WIS4WID) platform, and rewards are established on state transitions. Finally, both the experimental results in the laboratory and competition consequents of Follow Me Mission in robot@home league at RoboCup Japan Open 2013 Tokyo demonstrate that our robot May can fluently switch its poses to follow operator by utilizing the proposed schemes.
Starting Page	55
Ending Page	60
File Size	2590846
Page Count	6
File Format	PDF
ISBN	9781479903863
DOI	10.1109/iFuzzy.2013.6825409
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-06
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	4WIS4WD Fuzzy control Head Q-learning Wheels Home service robot Educational institutions Mobile communication Mobile robots Motion control TLD
Content Type	Text
Resource Type	Article

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