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The study and proposition of methods for the general Chance-Constrained qualitative state planning problem

Grant number: 13/26091-2
Support type:Scholarships abroad - Research
Effective date (Start): August 04, 2014
Effective date (End): August 03, 2015
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computer Systems
Principal researcher:Claudio Fabiano Motta Toledo
Grantee:Claudio Fabiano Motta Toledo
Host: Brian Charles Williams
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Research place: Massachusetts Institute of Technology (MIT), United States  

Abstract

The research project aims to study and propose methods of resolution for General Chance-Constrained State Planning Qualitative Problem with flexible scheduling and existence of obstacles. The problem has been established and is being studied by the team of Prof. Brian c. Williams in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT), motivated by the concept of a personal transport system model (autonomous vehicle) of the Boeing Company. The solution of this problem seeks to raise the level of interaction between human operators and the vehicle as treating automatically the uncertainties inherent in the planning of missions in a real environment. Mathematical models based on mixed integer linear programming (PLIM) were proposed in papers published by Prof. Brian c. Williams. The project will be executed by Prof. Claudio Fabian Motta Toledo during the period from 8/4/2014 to 8/3/2015 in CSAIL, as acceptance letter issued by MIT. The solutions can be validated in simulators and in real situations, considering the applications in autonomous vehicles developed at CSAIL/MIT and unmanned aerial vehicle (UAV) developed by Embedded and Evolutionary Systems group (EES) of the ICMC/USP. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
ARANTES, JESIMAR DA SILVA; ARANTES, MARCIO DA SILVA; MOTTA TOLEDO, CLAUDIO FABIANO; TRINDADE JUNIOR, ONOFRE; WILLIAMS, BRIAN CHARLES. Heuristic and Genetic Algorithm Approaches for UAV Path Planning under Critical Situation. International Journal on Artificial Intelligence Tools, v. 26, n. 1, SI, . (13/26091-2, 14/12297-0)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.