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Apresentação publica de proposta de Tese - CAT

20 Janeiro 2016, 11:12 - Maria João Silva Carvalho

Candidato: Daniel Luís Laurens Viegas

Título: Distributed state estimation for multiple autonomous vehicles

Orientador: Paulo Jorge Coelho Ramalho Oliveira

Co-Orientadores: Pedro Tiago Martins Batista

                             Carlos Jorge Ferreira Silvestre

 

25 de Janeiro de 2015, às 10:00 na Sala de Reuniões do DEEC

 

Abstract:

This thesis addresses problems on the subject of distributed state  estimation for multiple vehicles. In the scenarios that are envisioned, each vehicle must rely on measurements provided by sensors mounted on-board and limited communication with other vehicles to estimate relevant variables such as its own inertial position and linear velocity. The solutions that are developed put an emphasis in cooperation between vehicles, in the sense that only one or few vehicles have access to measurements of their own inertial position, while the rest rely on measurements of either their relative position or their range to other vehicles and the aforementioned limited communication to estimate their own state. For the case in which the vehicles have access to relative position measurements, the proposed distributed state observer features globally exponential stable estimation error dynamics with performance guarantees in the presence of noise in the measurements, and is able to cope with issues such as cycles in the measurement graph and time-varying measurement topologies. Regarding the case in which the vehicles have access to range measurements, conditions for global observability of the nonlinear dynamics of the problem are derived, and the proposed distributed state observer features error dynamics that converge exponentially fast to zero for any initial condition for acyclic measurement topologies. Simulation results for the practical application of a formation of Autonomous Underwater Vehicles (AUVs) working cooperatively are detailed for both cases to validate the theoretical results.