This paper presents the results of the experimental tests performed to validate the functionality of a variable pitch system (VPS), designed for pitch attitude control of the novel underwater robotic vehicle explorer UX-1. The VPS is composed of a mass suspended from a central rod mounted across the hull. This mass is rotated around the transverse axis of the vehicle in order to perform a change in the inclination angle for navigation in vertical mine shafts. In this work, the equations of motion are first derived with a quaternion attitude representation, and are then extended to include the dynamics of the VPS. The performance of the VPS is demonstrated in real underwater experimental tests that validate the pitch angle control independently, and coupled with the heave motion control system.

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.

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, Realtime 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.

This paper describes the UX-1 underwater mine exploration robotic system under development in the context of the UNEXMIN project. UNEXMIN is an international innovation action funded under the EU H2020 program, aiming to develop new technologies and services allowing the exploration of flooded underground mines. The system is comprised by the UX-1 robot prototype, launch and recovery system, command and control subsystem and a data management and post-processing computational infrastructure. The UX-1 robot is a small spherical robot equipped with a multibeam sonar, five digital cameras and rotating laser line structured light systems. It is capable of obtaining an accurate point cloud of the surrounding environment along with high resolution imagery. A set of mineralogy, water parameters and geophysical sensors was also developed in order to obtain a more comprehensive mine model. These comprise a multi-spectral camera, electro-conductivity, pH, magnetic field sensors, a subbottom sonar, total natural gamma-ray detector, UV-light for fluorescent observation and a water sampling unit. The design of the system is presented along with the robot design. Some preliminary results are also presented and discussed.

This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.

In this article, we describe the analysis, design and implementation of a control architecture for a mobile platform to autonomously carry out transportation, surveillance and inspection tasks in semi-structured industrial environments. Based on a hierarchical structure composed by the organization, coordination and functional levels organized linguistically and structured according to the principle of increasing precision with decreasing intelligence, this control architecture permits the real-time parallel execution of tasks.