The problem of estimating the position of a 3-D vehicle subject to a constant unknown velocity disturbance is addressed: the only available model output is assumed to be the distance (range) to a reference point. The vehicle's nominal velocity is also assumed to be known. An observability analysis is performed and an observer is designed. The proposed approach departs from alternative ones and leads to the definition of a linear time-invariant state equation with a linear time-varying output. The localization problem is solved using a novel outlier robust predictor-corrector state estimator. Numerical simulation examples are described to illustrate the performance of the method compared with a standard Kalman filter.

The Widely scalable Mobile Underwater Sonar Technology (WiMUST) project is an H2020 Research and Innovation Action funded by the European Commission. The project aims at developing a system of cooperative autonomous underwater vehicles (AUVs) for geotechnical surveying and geophysical exploration. The paper describes the main objectives of the project, gives an overview of the methodologies adopted to achieve them, and summarizes the work done in the first year of R&D work.

In this paper, we present DexROV, an EC Horizon 2020-funded project that proposes to implement novel operation strategies for underwater semiautonomous interventions. These costly and demanding operations are increasingly performed by remotely operated vehicles (ROVs), contributing to risk cutting for human divers. However, ROV operations require offshore structures, hosted on a support vessel with a crew of a significant amount of personnel necessary to properly handle and operate the robotic platform. One of the key goals of DexROV is to delocalize on shore the manned support as much as possible, reducing the crew onboard the support vessel and consequently the costs and risks of the whole operation. The control center is located onshore, far from the actual operation location. Operators interact with the ROV through a simulation environment that exploit 3D models of the environment built online relying on the perception and modeling capabilities of the robotic system and transmitted via satellite communication. Currently, ROVs lack the dexterous capabilities needed to perform many kinds of operations, for which human divers are still necessary. DexROV addresses this problem, equipping the ROV with two 6 DOF (degrees of freedom) dexterous manipulators with anthropomorphic end-effectors and providing semiautonomous capabilities. The control will rely on a multitask priority approach that will help the operator to focus on the main operation, leaving the low-level tasks to be autonomously performed by the ROV.

The operation of a ROV requires significant off-shore dedicated manpower to handle and operate the robotic platform. In order to reduce the burden of operations, DexROV proposes to work out more cost effective and time efficient ROV operations, where manned support is in a large extent delocalized onshore (i.e. from a ROV control center), possibly at a large distance from the actual operations, relying on satellite communications. The proposed scheme makes provision for advanced dexterous manipulation capabilities, exploiting human expertise from a remote location when deemed useful. The outcomes of the project will be integrated and evaluated in a series of tests and evaluation campaigns, culminating with a realistic deep sea (1,300 meters) trial. After one year, the project specified the system architecture of the system and carried out preliminary technological trade-offs for the subsystems