• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Master's Dissertation
DOI
10.11606/D.3.2016.tde-17062016-142254
Document
Author
Full name
Daniel Chin Min Wei
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2015
Supervisor
Committee
Fonseca Junior, Edvaldo Simões da (President)
Schaal, Ricardo Ernesto
Veiga, Luís Augusto Koenig
Title in Portuguese
Método de desvio de obstáculos aplicado em veículo autônomo.
Keywords in Portuguese
Desvio de obstáculos
Sensor ultrassônico
Veículo autônomo
Veículos especiais
Veículos guiados remotamente
Abstract in Portuguese
A operação de veículos autônomos necessita de meios para evitar colisões quando obstáculos não conhecidos previamente são interpostos em sua trajetória. Algoritmos para executar o desvio e sensores apropriados para a detecção destes obstáculos são essenciais para a operação destes veículos. Esta dissertação apresenta estudos sobre quatro algoritmos de desvio de obstáculos e tecnologia de três tipos de sensores aplicáveis à operação de veículos autônomos. Após os estudos teóricos, um dos algoritmos foi testado para a comprovação da aplicabilidade ao veículo de teste. A etapa experimental foi a realização de um programa, escrito em linguagem de programação Java, que aplicou o algoritmo Inseto 2 para o desvio de obstáculos em uma plataforma robótica (Robodeck) com o uso de sensores ultrassônicos embarcados na referida plataforma. Os experimentos foram conduzidos em ambiente fechado (indoor), bidimensional e horizontal (plano), fazendo o Robodeck executar uma trajetória. Para os testes, obstáculos foram colocados para simular situações variadas e avaliar a eficácia do algoritmo nestas configurações de caminho. O algoritmo executou o desvio dos obstáculos com sucesso e, quando havia solução para a trajetória, ela foi encontrada. Quando não havia solução, o algoritmo detectou esta situação e parou o veículo.
Title in English
Collision avoidance methods applied in an autonomous vehicle.
Keywords in English
Driverless vehicle
Obstacle avoidance
Ultrasonic sensors
Abstract in English
The operation of autonomous vehicles need means to avoid collisions when unforeseen obstacles are posed in its trajectory. Algorithms to perform the deviation and suitable sensors for detecting these obstacles are essential for the operation of such vehicles. This dissertation presents studies on four obstacle avoidance algorithms and technology of three types of sensors applicable to the operation of autonomous vehicles. After the theoretical studies, one of the algorithms has been tested for evidence of applicability to the test vehicle. The experimental phase was the implementation of a program written in Java programming language, which applied the Insect 2 algorithm for obstacle avoidance in a robotic platform (Robodeck) using ultrasonic sensors embedded in the platform. The experiments were conducted in a closed environment (indoor), two-dimensional and flat, making Robodeck perform a trajectory. For testing, obstacles were placed to simulate various situations and evaluating the algorithm efficacy for these path configurations. The algorithm successfully performed the deviation of obstacles and, when there was a solution to the trajectory, it was found. When there was no solution, the algorithm has detected this situation and stopped the vehicle.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
Publishing Date
2016-06-21
 
WARNING: Learn what derived works are clicking here.
All rights of the thesis/dissertation are from the authors
CeTI-SC/STI
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2021. All rights reserved.