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

• Grant number: 13/26091-2
• Support Opportunities: 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 Investigator: Claudio Fabiano Motta Toledo
• Grantee: Claudio Fabiano Motta Toledo
• Host Investigator: Brian Charles Williams
• Host 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)

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, FEB 2017. (13/26091-2, 14/12297-0)