PPGINF PÓS-GRADUAÇÃO EM ENGENHARIA DA INFORMAÇÃO FUNDAÇÃO UNIVERSIDADE FEDERAL DO ABC Phone: Not available http://propg.ufabc.edu.br/ppginfo

Banca de QUALIFICAÇÃO: SERGIO POLIMANTE SOUTO

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : SERGIO POLIMANTE SOUTO
DATA : 02/08/2019
HORA: 14:00
LOCAL: sala 303, 3º andar, Bloco B, Campus SA da Fundação Universidade Federal do ABC, localizada na Avenida dos Estados, 5001, Santa Terezinha, Santo André, SP
TÍTULO:

Multiobjective optimization of routes and trajectories for UAVs


PÁGINAS: 66
GRANDE ÁREA: Engenharias
ÁREA: Engenharia Elétrica
RESUMO:

The small autonomous aerial vehicles are becoming popular in civil applications such as imaging, surveillance, mapping and others, due to the advancements in electronics and mechatronics technology and also due to the
popularization of innovative means of production such as 3D printing. However, these vehicles have limitations on their operational capability due to low energy capacity (for rotary wings type) and severe kinematic constraints (for fixed wings type). A method capable of planning missions energetically more efficient that
takes into consideration the kinematic constraints of autonomous aerial vehicles is fundamental to expand this technology deployment capability. The methods available nowadays are able to plan missions for multiple waypoints optimizing the route, but not the trajectory. The methods that are able to optimize trajectory taking into consideration the kinematic constraints of the vehicle does not take into consideration multiple waypoints. This present study aims to implement an algorithm capable of planning optimized missions for autonomous aerial vehicle considering multiple waypoints the specific kinematic constraints of different vehicles such as maximum rotation, maximum torsion and maximum climbing angle using bending elastic energy. The trajectory optimization also considers the total length of the curve. The routes are modeled as the Travelling Salesman
Problem, and the trajectories are modeled as Bézier curves. Genetics Algorithms are employed in order to optimize the models. Preliminary results show that it is possible to optimize routes using TSP and GA to sub optimal values with up to 0,36% error from optimal value. It also has been possible to optimize trajectory to specific kinematic constraints of the vehicle and the total length of the trajectory. The Pareto front of the multiobjective optimization is analyzed. The future work will be focused on integrating both solutions for route and trajectory optimization. It will be conducted tests on virtual vehicles and both fixed and rotary winged  physical vehicles.


MEMBROS DA BANCA:
Presidente - Interno ao Programa - 1603840 - JOAO HENRIQUE KLEINSCHMIDT
Membro Titular - Examinador(a) Interno ao Programa - 2090028 - FILIPE IEDA FAZANARO
Membro Titular - Examinador(a) Externo ao Programa - 3044516 - LUNEQUE DEL RIO DE SOUZA E SILVA JUNIOR
Membro Suplente - Examinador(a) Interno ao Programa - 2196309 - CARLOS ALBERTO KAMIENSKI
Notícia cadastrada em: 27/06/2019 14:53
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