Daniela De Palma

Advanced ROV Autonomy for Efficient Remote Control in the DexROV Project

In this paper, we present DexROV, a funded EC Horizon 2020 project that proposes to implement novel operation strategies for underwater semi-autonomous interventions. These costly and demanding operations are more and more often performed by ROVs (Remotely Operated Vehicles), contributing to risks 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 whole operation costs and risks. The Control Center is located onshore, far away 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 kind 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 semi-autonomous capabilities. The control will rely on a multi-task 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.

Single Range Localization in 3-D: Observability and Robustness Issues

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 vehicles 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.

Widely scalable mobile underwater sonar technology: An overview of the H2020 WiMUST project

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 reports about the first year activities and it gives an overview of the main objectives and methods.