Repositório do Conhecimento Institucional do Centro Universitário FEI
 

Engenharia de Robôs

URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/339

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2004 - 20062

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Autor: search.filters.author.Flavio TonidandelData final: 2008

Resultados da Pesquisa

Agora exibindo 1 - 2 de 2
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    Artigo de evento 1 Citação(ões) na Scopus
    A Case Base Seeding for Case-Based Planning Systems
    (2004-12-26) Flavio Tonidandel; RILLO, M.
    This paper describes a Case Base Seeding system (CBS) that can be used to seed a case base with some random cases in order to provide minimal conditions for the empirical tests of a Case-Based Planning System (CBP). Random case bases are necessary to guarantee that the results of the tests are not manipulated. Although these kind of case bases are important, there are no references about CBS systems in the literature even from those CBP systems that claim to use some similar systems. Therefore, this paper tries to overcome this deficiency by modeling and implementing a complete random Case Base Seeding process. © Springer-Verlag Berlin Heidelberg 2004.
  • N/D
    Artigo de evento 1 Citação(ões) na Scopus
    A fast model-based vision system for a robot soccer team
    (2006-11-17) MARTINS, M. F.; Flavio Tonidandel; Reinaldo Bianchi
    Robot Soccer is a challenging research domain for Artificial Intelligence, which was proposed in order to provide a long-term problem in which researchers can investigate the construction of systems involving multiple agents working together in a dynamic, uncertain and probabilistic environment, to achieve a specific goal. This work focuses on the design and implementation of a fast and robust computer vision system for a team of small size robot soccer players. The proposed system combines artificial intelligence and computer vision techniques to locate the mobile robots and the ball, based on global vision images. To increase system performance, this work proposes a new approach to interpret the space created by a well-known computer vision technique called Hough Transform, as well as a fast object recognition method based on constraint satisfaction techniques. The system was implemented entirely in software using an off-the-shelf frame grabber. Experiments using real time image capture allows to conclude that the implemented system are efficient and robust to noises and lighting variation, being capable of locating all objects in each frame, computing their position and orientation in less than 20 milliseconds. © Springer-Verlag Berlin Heidelberg 2006.