Title :
Autonomous target tracking by Twin-Burger 2
Author :
Balasuriya, Arjuna ; Ura, Tamaki
Author_Institution :
Sch. of EEE, Nanyang Technol. Univ., Singapore
Abstract :
In this paper, a sensor fusion technique is proposed for autonomous underwater vehicles (AUV) to track underwater cables. The work presented here is an extension of the authors´ previously proposed vision based cable tracking system (1997, 1998). The focus of this paper is to solve the two practical problems encountered in vision based systems; namely (1) navigation of AUV when cable is invisible in the image, and (2) selection of the correct cable (interested feature) when there are many similar features appearing in the image. The proposed sensor fusion scheme uses deadreckoning position uncertainty with a 2D position model of the cable to predict the region of interest in the image. This reduces the processing data increasing processing speed and avoids tracking other similar features appearing in the image. The proposed method uses a 2D position model of the cable for AUV navigation when the cable features are invisible in the predicted region. An experiment is conducted to test the performance of the proposed system using the AUV “Twin-Burger 2”. The experimental results presented in this paper shows how the proposed method handles the above mentioned practical problems
Keywords :
mobile robots; sensor fusion; submarine cables; target tracking; underwater vehicles; 2D position model; AUV; AUV navigation; Twin-Burger 2; autonomous target tracking; autonomous underwater vehicles; cable selection; dead reckoning; deadreckoning position uncertainty; navigation; sensor fusion scheme; sensor fusion technique; underwater cable tracking; Focusing; Machine vision; Navigation; Predictive models; Sensor fusion; Target tracking; Uncertainty; Underwater cables; Underwater tracking; Underwater vehicles;
Conference_Titel :
Intelligent Robots and Systems, 2000. (IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
0-7803-6348-5
DOI :
10.1109/IROS.2000.893125