# MViDO: A High Performance Monocular Vision-Based System for Docking A Hovering AUV
## 1 Introduction  
This work presents a monocular vision-based system for a hovering Autonomous Underwater Vehicle (AUV) in the context of the autonomous docking process. In this work, 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. It was intended to realize how far we can get by using only the image in determining the relative pose and tracking the target. Space limitations onboard the AUV and energy limitations dictated the requirements for the development of this work. Based only on the data collected by a low-cost camera it was possible to reach a guidance law that drives the AUV to the cradle of a docking station. 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 20 Hz and it is not desired that there is more than one estimation between two consecutive frames. As can be seen from the results (Section 5, Section 5.2.2, Figure 31), this objective has been achieved. The detector and relative pose estimation algorithm provides 12 frames per second (83 ms) to which adds the processing time of the developed filter which for 1000 particles per marker occupies 13 ms of the total processing time. We propose algorithms that should be able to run in alow power consumption and low-cost system with minimal interference with existing HW modules of AUV MARES [1]. Being our goal to develop high-level algorithms and not to develop hardware, we have chosen a generic platform called Raspberry Pi 2, which we can classify in general as a low power consumption and low-cost system. So, instead of considering data sources from other sensors and increase the computation cost for sensor fusion, we choose to explore the maximum capabilities of data provided by the image sensor, as we will explain at Section 2. Our approach, considering Raspberry Pi 2 processing constraints, should be able to get more than 10 estimations per second (a requirement for smooth control of MARES). In this work, in addition to presenting the developed vision-based system that detects and tracks the docking station visual markers, we also address the problem of defining a guidance law for a hovering AUV when performing a docking maneuver. We used as a case study the docking of MARES, a small size modular AUV [1], but our approach is pretty general and can be applied to any hovering vehicle. 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. This work has started with the localization and positioning of an Autonomous Surface Vehicle (ASV), assuming parallel target and camera planes [2]. Then the efforts were devoted to the preliminary characterization of relative position estimation and vehicle positioning. In that work [3], it was demonstrated that the hovering AUV MARES (Figure 1) was capable to track and position itself with regard to the target, at a given pre-specified depth. The estimation of the relative position, based solely on the image, is subject to abrupt variations as well as indeterminate solutions in the absence of one of the markers. There was a need to persist with the tracking even in the case of partial or momentary occlusions of the markers that compose the target. The solution we found to overcome this problem is presented on Section 2 (Section 2.3). The proposed solution allowed not only to maintain the estimates of the relative pose even during the occlusion of one or more markers, but also to reduce the number of outliers detections (Section 5). In order to drive the AUV MARES from any point within the camera field of view to the point where the cradle of the docking station is, we designed and developed a guidance law (Section 4). The proposed law allows always keeping the markers in line of sight during the docking maneuver.