Abstract
The growing economic interest in the exploitation of mineral resources on deep-ocean beds, including those in the vicinity of sensitive-rich habitats such as hydrothermal vents, raise amounting concern about the damage that such actions might originate to these poorly-know ecosystems, which represent millions of years of evolution and adaptations to extreme environmental conditions. It has been suggested that mining may cause a major impact on vent ecosystems and other deep-sea areas. Yet, the scale and the nature of such impacts are unknown at present. Hence, building upon currently available scientific information it is crucial to develop new cost-effective technologies embedded into rigorous operating frameworks. The forward-thinking provided here will assist in the development of new technologies and tools to address the major challenges associated with deep sea-mining; technologies for in situ and ex situ observation and data acquisition, biogeochemical processes, hazard assessment of deep-sea mining to marine organisms and development of modeling tools in support of risk assessment scenarios. These technological developments are vital to validate a responsible and sustainable exploitation of the deep-sea mineral resources, based on the precautionary principle.

Abstract

Abstract
We present a novel approach of Stereo Visual Odometry for vehicles equipped with calibrated stereo cameras. We combine a dense probabilistic 5D egomotion estimation method with a sparse keypoint based stereo approach to provide high quality estimates of vehicle's angular and linear velocities. To validate our approach, we perform two sets of experiments with a well known benchmarking dataset. First, we assess the quality of the raw velocity estimates in comparison to classical pose estimation algorithms. Second, we added to our method's instantaneous velocity estimates a Kalman Filter and compare its performance with a well known open source stereo Visual Odometry library. The presented results compare favorably with state-of-the-art approaches, mainly in the estimation of the angular velocities, where significant improvements are achieved.

Abstract
In this paper we propose a novel fully probabilistic solution to the stereo egomotion estimation problem. We extend the notion of probabilistic correspondence to the stereo case which allow us to compute the whole 6D motion information in a probabilistic way. We compare the developed approach against other known state-of-the-art methods for stereo egomotion estimation, and the obtained results compare favorably both for the linear and angular velocities estimation.

Abstract
The fish farming industry is becoming widespread all over the world. By 2039 most of the fish we eat will come from the fish farming industry. In this work, we propose an autonomous robotic solution for indoor fish farming biomass estimation. Our proposed system moves silently on top of the tank borders using differential wheels and a structured light vision system (SLS). The SLS system is composed by a camera and two line lasers (projectors) equipped with a line beam that allows to obtain the fish depth profile present in the tank to perform biomass estimation. Results in laboratory and in real aquaculture environment with live fish are presented.

Abstract
Underwater experiments with unmanned vehicles are complex, costly, time-consuming and in some circumstances potentially dangerous, involving the risk of losing or damaging the robots. The nature of the underwater environment, makes it very difficult, for researchers, to observe the evolution of the running system. Simulators are useful tools for the development of unmanned vehicle software, algorithm benchmarking and system preliminary validation. In this work, the problem of simulating a complex underwater scenario for marine robotics and a comparative analysis of simulators for marine robotics are presented. Relevant sensors for underwater robots under development, such as multibeam and imaging 2D sonar were implemented in two simulators and tested in a realistic experimental scenario like a flooded mine.