Jose Villa Escusol: Solving the challenges of a co-operative autonomous offshore system
Autonomous algorithm implementation in any vehicle requires multiple steps before completing the mission, especially in marine environments, as they remain very labour-intensive and expensive activities. This interest in offshore interventions includes numerous activities, such as search and rescue missions, seabed explorations, target detection, or offshore surveillance.
The offshore system involves autonomous boats and submarines as the primary offshore vehicles. In the guidance, navigation and control architecture, situational awareness and mission control are crucial for the operation of the offshore vehicles. A modular and multi-layer architecture can provide a computationally cheap and easy implementation for the required autonomous capabilities.
In his thesis, Jose Villa Escusol has proposed an architecture to solve the design, modelling, and implementation challenges of a path-following algorithm with obstacle avoidance capabilities for a co-operative autonomous system. This co-operative system employs an unmanned surface vehicle and an autonomous underwater vehicle.
“The development of an analogous guidance, navigation, and control architecture for autonomous offshore vehicles will enable simple and easy connectivity and shared intelligence between multiple offshore vehicles,” says Jose Villa Escusol.
The doctoral dissertation of M.Sc. Jose Villa Escusol in the field of Mechanical and Production Engineering titled A Guidance, Navigation, and Control Architecture for a Co-operative Autonomous Offshore System will be publicly examined in the Faculty of Engineering and Natural Sciences at Tampere University at 12.15 pm on Friday 1st of October 2021 in the auditorium K1702 of Konetalo (Korkeakoulunkatu 6, Tampere). The Opponents will be Associate Prof. Kari Tammi from Aalto University, Finland, and Prof. Luc Jaulin from University Bretagne Occidentale, France. The Custos will be Prof. Kari T. Koskinen from the Faculty of Engineering and Natural Sciences.
The event can be followed via remote connection.
The dissertation is available online at the http://urn.fi/URN:ISBN:978-952-03-2097-3.