Abstract
This paper presents a high performance (low computationally demanding) monocular vision-based system for a hovering Autonomous Underwater Vehicle (AUV) in the context of autonomous docking process-MViDO system: Monocular Vision-based Docking Operation aid. The MViDO consists of three sub-modules: a pose estimator, a tracker and a guidance sub-module. The system is based on a single camera and a three spherical color markers target that signal the docking station. The MViDO system allows the pose estimation of the three color markers even in situations of temporary occlusions, being also a system that rejects outliers and false detections. This paper also describes the design and implementation of the MViDO guidance module for the docking manoeuvres. We address the problem of driving the AUV to a docking station with the help of the visual markers detected by the on-board camera, and show that by adequately choosing the references for the linear degrees of freedom of the AUV, the AUV is conducted to the dock while keeping those markers in the field of view of the on-board camera. The main concepts behind the MViDO are provided and a complete characterization of the developed system is presented from the formal and experimental point of view. To test and evaluate the MViDO detector and pose an estimator module, we created a ground truth setup. To test and evaluate the tracker module we used the MARES AUV and the designed target in a four-meter tank. The performance of the proposed guidance law was tested on simulink/Matlab.
Highlights
This work presents a monocular vision-based system for a hovering Autonomous UnderwaterVehicle (AUV) in the context of the autonomous docking process
In addition to presenting the developed vision-based system that detects and tracks the docking station visual markers, we address the problem of defining a guidance law for a hovering Autonomous Underwater Vehicle (AUV) when performing a docking maneuver
The results presented in this paper are the outcome of continuous effort made by the center for robotics at INESC TEC for autonomous docking of AUVs
Summary
This work presents a monocular vision-based system for a hovering Autonomous UnderwaterVehicle (AUV) in the context of the autonomous docking process. We developed a complete approach to bring a hovering AUV to a docking station using only one sensor: a single camera. The aim was to explore the development of a system to assist autonomous docking based on a single cost-effective sensor only. This work was intended to observe the target at a rate of 10 frames per second minimum (processing time less than 100 ms). This is due to the fact that the control operates at 20Hz and it is not desired that there is more than one estimation between two consecutive frames. We propose algorithms that should be able to run in a
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