Robust Face Tracking Control of a Mobile Robot Using Self-Tuning Kalman Filter and Echo State Network

doi:10.1002/asjc.204

淡江大學機構典藏 > 工學院 > 電機工程學系暨研究所 > 期刊論文 > Item 987654321/55038

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題名:	Robust Face Tracking Control of a Mobile Robot Using Self-Tuning Kalman Filter and Echo State Network
作者:	Tsai, Chi-yi;Xavier Dutoit;Song, Kai-tai;Hendrik Van Brussel;Marnix Nutti
貢獻者:	淡江大學電機工程學系
關鍵詞:	Visual tracking control;visual state estimation;echo state network;face tracking;illumination variation
日期:	2010-07
上傳時間:	2011-08-09 20:29:51 (UTC+8)
出版者:	Hoboken: Wiley-Blackwell Publishing, Inc.
摘要:	This paper presents a novel design of face tracking algorithm and visual state estimation for a mobile robot face tracking interaction control system. The advantage of this design is that it can track a user's face under several external uncertainties and estimate the system state without the knowledge about target's 3D motion-model information. This feature is helpful for the development of a real-time visual tracking control system. In order to overcome the change in skin color due to light variation, a real-time face tracking algorithm is proposed based on an adaptive skin color search method. Moreover, in order to increase the robustness against colored observation noise, a new visual state estimator is designed by combining a Kalman filter with an echo state network-based self-tuning algorithm. The performance of this estimator design has been evaluated using computer simulation. Several experiments on a mobile robot validate the proposed control system.
關聯:	Asian Journal of Control 12(4), pp.488-509
DOI:	10.1002/asjc.204
顯示於類別:	[電機工程學系暨研究所] 期刊論文

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