Abstract
This paper addresses a three-dimensional (3D) reconstruction of a flooded open pit mine with an autonomous surface vehicle (ASV) and unmanned aerial vehicle (UAV). The ROAZ USV and the Otus UAV were used to provide the underwater bathymetric map and aerial 3D reconstruction based from image data. This work was performed wihtin the context of the European researcj project VAMOS with the objective of developing robotic tools for efficient underwater mining

Abstract
This work presents a low cost RTK-GPS system for localization of unmanned surface vehicles. The system is based on the use of standard low cost L1 band receivers and in the RTKlib open source software library. Mission scenarios with multiple robotic vehicles are addressed as the ones envisioned in the ICARUS search and rescue case where the possibility of having a moving RTK base on a large USV and multiple smaller vehicles acting as rovers in a local communication network allows for local relative localization with high quality. The approach is validated in operational conditions with results presented for moving base scenario. The system was implemented in the SWIFT USV with the ROAZ autonomous surface vehicle acting as a moving base. This setup allows for the performing of a missions in a wider range of environments and applications such as precise 3D environment modeling in contained areas and multiple robot operations.

Abstract
This paper describes the calibration of an underwater navigation system in enclosed scenarios. The work was performed in the context of the VAMOS project addressing the development of robotic solutions for flooded open pit mine exploration. An algorithm for calibration of extrinsic parameters for DVL and USBL systems is presented. Field experiments were performed with the ROAZ autonomous surface vehicle equipped with the underwater sensors and using precision IMU/GNSS fused data as groundtruth. The tests were performed in Douro River and in the Bejanca open pit mine, one of the VAMOS test sites, both in northern Portugal. The procedure was validated in the operational scenarios and results are presented showing the error correction and navigation quality improvement.

Abstract
This paper presents EVA, a new concept for an hybrid ROV/AUV designed to support the underwater operation of an underwater mining machine, developed in the context of the European H2020 R&D VAMOS Project. This project is briefly presented, introducing the main components and concepts, providing the reader with clear picture of the operational scenario and allowing to understand better the functionality requirements of the support robotic vehicle developed. The design of EVA is detailed presented, addressing the mechanical design, hardware architecture, sensor system and navigation and control. The results of EVA both in water test tank, in the ! VAMOS! Field trials in Lee Moor, UK, and in an harbor scenario are presented and discussed

Abstract
Limited perception capabilities underwater shrink the envelope of effective localization techniques that can be applied in this environment. Long-term localization in six degrees of freedom can only be achieved by combining different sources of information. A multiple vehicle underwater localization solution, for localizing an underwater mining vehicle and its support vessel, is presented in this paper. The surface vessel carries a short baseline network, that interact with the inverted ultra-short baseline, carried by the underwater mining vehicle. A multiple antenna GNSS system provides data for localizing the surface vessel and to georeference the short baseline array. Localization of the mining vehicle results from a data fusion approach, that combines multiple sources of sensor information using the Extended Kalman Filter (EKF) framework. The developed solutions were applied in the context of the VAMOS! European project. Long-term real time position errors below 0.2 meters, for the underwater machine, and 0.02 meters, for the surface vessel, were accomplished in the field. All presented results are based on data acquired in a real scenario.

Abstract
This paper presents the positioning, navigation and awareness (PNA) system developed for the Underwater Robotic Mining System of the VAMOS! project [1]. It describes the main components of the VAMOS! system, the PNA sensors in each of those components, the global architecture of the PNA system, and its main subsystems: Position and Navigation, Real-time Mine Modeling, 3D Virtual reality HMI and Real-time grade system. General results and lessons learn during the first mining field trial in Lee Moor, Devon, UK during the months of September and October 2017 are presented.