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Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches
United Technologies Research Center, No. 3239, Shenjiang Road, Shanghai 201206, P.R. China
Department of Mechanical Engineering, Massachusetts Institute of Technology, MA, USA
Faculty of Engineering, University of Technology, Sydney, NSW, Australia
* Author to whom correspondence should be addressed.
Received: 31 August 2008; in revised form: 22 November 2008 / Accepted: 28 November 2008 / Published: 15 December 2008
Abstract: This paper surveys the developments of last 10 years in the area of vision based target tracking for autonomous vehicles navigation. First, the motivations and applications of using vision based target tracking for autonomous vehicles navigation are presented in the introduction section. It can be concluded that it is very necessary to develop robust visual target tracking based navigation algorithms for the broad applications of autonomous vehicles. Then this paper reviews the recent techniques in three different categories: vision based target tracking for the applications of land, underwater and aerial vehicles navigation. Next, the increasing trends of using data fusion for visual target tracking based autonomous vehicles navigation are discussed. Through data fusion the tracking performance is improved and becomes more robust. Based on the review, the remaining research challenges are summarized and future research directions are investigated.
Keywords: Computer Vision; Autonomous Vehicles; Mobile Robots; Target Tracking; Navigation; Sensor Data Fusion
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Cite This Article
MDPI and ACS Style
Jia, Z.; Balasuriya, A.; Challa, S. Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches. Algorithms 2008, 1, 153-182.
Jia Z, Balasuriya A, Challa S. Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches. Algorithms. 2008; 1(2):153-182.
Jia, Zhen; Balasuriya, Arjuna; Challa, Subhash. 2008. "Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches." Algorithms 1, no. 2: 153-182.