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Hybrid qualitative state plan problem and mission planning with UAVs

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Author(s):
Márcio da Silva Arantes
Total Authors: 1
Document type: Doctoral Thesis
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB)
Defense date:
Examining board members:
Cláudio Fabiano Motta Toledo; Paulo Morelato França; Reinaldo Morabito Neto; Maristela Oliveira dos Santos
Advisor: Cláudio Fabiano Motta Toledo
Abstract

This paper aims to present the thesis developed in the Doctoral Programin Computer Science and Computational Mathematics of the ICMC/USP. The thesis theme seeks to advance the state of the art by solving the problems of scalability and representation present in mission planning algorithms for Unmanned Aerial Vehicle (UAV). Techniques based on mathematical programming and evolutionary computation are proposed. Articles have been published, submitted or they are in final stages of preparation.These studies report the most significant advances in the representation and scalability of this problem. Mission planners worked on the thesis deal with stochastic problems in non-convex environments,where collision risks or failures in mission planning are treated and limited to a tolerated value. The advances in the representation allowed to solve violations in the risks present in the original literature modeling, besides making the models more realistic when incorporating aspects such as effects of the air resistance. Efficient mathematical modeling techniques allowed to advance from a Mixed Integer Nonlinear Programming (MINLP) model, originally proposed in the literature, to a Mixed Integer Linear Programming (MILP) problem. Modeling as a MILP led to problem solving more efficiently through the branch-and-algorithm. The proposed new representations resulted in improvements from scalability, solving more complex problems within a shorter computational time. In addition, advances in scalability are even more effective when techniques combining mathematical programming and metaheuristics have been applied to the problem. (AU)

FAPESP's process: 14/11331-0 - Hybrid qualitative state plan and mission planning problem with UAVs
Grantee:Márcio da Silva Arantes
Support type: Scholarships in Brazil - Doctorate