Guidance system for autonomous underwater vehicles in confined environments
- Autores: Zoran Milosevic
- Directores de la Tesis: Claudio Rossi (dir. tes.), Sergio Domínguez Cabrerizo (dir. tes.)
- Lectura: En la Universidad Politécnica de Madrid ( España ) en 2021
- Idioma: español
- Materias:
- Enlaces
- Tesis en acceso abierto en: Archivo Digital UPM
- Resumen
Innovation and technological developments have always played an essential role in breakthroughs in science. The use of unmanned underwater vehicles (UUV) has revolutionized aquatic exploration in the last decades. UUVs can be deployed at depths and in environments that are inaccessible to humans, and can gather data that cannot be obtained in any other way.
In the recent years, there has been a growing interest in re-opening abandoned mine sites across Europe, which may contain raw materials that are currently in critical demand, whose exploitation would reduce Europe's dependency on external sources. A recent survey on abandoned mines in Europe collected data regarding 30000 mine sites, with more than 8000 sites being flooded. This thesis contributes to the innovative solutions developed within the framework of the UNEXMIN project, born with the aim of exploring those flooded sites and wherein a novel underwater platform system, named UX-1, has been designed. The UX-1 robot needs to navigate completely autonomously, as no communications are possible, in the 3D networks of unknown mine tunnels and gather various geoscientific data. The development of the novel platform, intended to perform in challenging environments, requires innovative design approaches for its software and hardware modules.
The main research goal of this thesis is the design, implementation and validation of the autonomous guidance system of the UX-1 underwater robot. The novel mechanical design of the robot and its distinctive on-board scientific instrumentation represent specific features of this platform. The coordination of such instrumentation with the movement of the submersible itself, fulfilling the strict positional requirements of the scientific sample capturing for each type of sensor, must be ensured by the guidance system of the platform. For these reasons, the design and implementation of the guidance system of the UX-1 constitute a unique research challenge.
Furthermore, to ensure long-term autonomy, a sufficient degree of resilience is required in order to keep and recover the operation functionality of the system when disrupted by unexpected events. To this effect, an advanced knowledge-based self-awareness technique, named metacontrol, has been developed. The metacontroller has been designed to increase the autonomy of the robot by enhancing its fault tolerance capabilities. A self-diagnosis module is used to determine the status of the robot, and a decision-making module is used to choose the best reconfiguration of the whole robot system for optimal functioning according to the previous diagnosis.
The proposed solutions are experimentally validated in complex scenarios using simulation, software-in-the-loop (SIL), and hardware-in-the-loop (HIL) approaches, designed to reproduce with an increasing degree of fidelity the navigation in mine tunnel environments. HIL experiments, representing the highest degree of fidelity, required the integration of real hardware and software modules, including our guidance system, with partially simulated environmental readings. The experiments were performed in a water pool, wherein the real readings related to its positioning were used for navigation and control purposes, while the mapping sensors reading were bypassed in order to replicate different mine tunnel structures. The results obtained in these tests demonstrate the effectiveness of the guidance system and its proper integration with the rest of the systems of the robot, and validate the abilities of the UX-1 platform to perform complex missions in flooded mine environments.
