Surface reconstruction from parallel cross sections is an important problem in medical imaging and other object-modeling applications. Shape and topological differences between object contours in adjacent sections cause severe difficulties in the reconstruction process. A way to approach this problem is using the skeleton to create intermediate sections that represent the place where the ramifications occur. Several authors have proposed previously the use of some type of skeleton to face the problem, but in an intuitive way and without giving a basis that guarantees a complete and correct use. In this paper, the foundations of the use of the skeleton to reconstruct a surface from cross sections are expounded. Some results of an algorithm that is based on these foundations and has been recently proposed by the authors are shown that illustrate the excellent performance of the method in especially difficult cases not solved previously.
Se presenta un nuevo método para localizar a personas en entornos urbanos usando robots móviles sociales que trabajan de manera cooperativa, el cual supera las limitaciones de enfoques ya existentes, que se adaptan a entornos específicos, o se basan en comportamientos humanos poco re- alistas. Con este método cooperativo los robots pueden encontrar a personas fuera del campo de rango de sensores u ocultados por obstáculos dinámicos o estáticos. Nuestro enfoque incluye la búsqueda de personas, seguimiento, cooperación multi-robot y comunicación. En particular se define un “Cooperative Highest-Belief Continuous Real-time POMCP” que puede ejecutarse en tiempo real y en entornos continuos y grandes. En este método se usan algoritmos de búsqueda on-line Partially Observable Monte-Carlo Planning (POMCP), los cuales, al contrario de trabajos anteriores son capaces de planificar con incertidumbre y con grandes espacios de estados. La estrategia de búsqueda hace un balanceo entre la probabilidad de que la persona esté en una posición concreta, la distancia de las posiciones, y si la posición está cerca de una meta ya asignada a otro robot. Se ha validado el método con extensivo número de simulaciones y experimentos reales con una persona y dos robots.
The principal steps of a new method to solve the problem of surface reconstruction from parallel cross sections are presented in this paper. This method constitutes the extension of one previously proposed by the authors using the skeleton to solve the investigation problem. The method guarantees the correct topology of the surface without altering the original contours. Some results are shown that illustrate the excellent performance of the method in particular difficult cases not solved previously. All the cases analyzed are manipulated in the same way. In real cases, the global time complexity improves the quadratic time of the quickest consulted methods.
The game of Scrabble has been successfully tackled by two engines: Quackle and Maven. They attain the state-of-the-art in Computer Scrabble. These engines use simulation techniques and precalculated values to achieve superhuman play. This paper presents a Scrabble-playing engine, Heuri, which achieves world championship standards when playing in Spanish, and a very high level when playing in English and French, without using brute-force approaches.One advantage of Heuri is that its calculations, as opposed to many in Quackle, are not precomputed and instead performed for every turn. Spanish match results of different versions of Heuri against humans and two versions of Quackle are presented in this paper. Results against Quackle, in English and French, are also given. The main goal of this paper is to enrich Computer Scrabble with the description of a Scrabble playing program, Heuri, which is differently designed from earlier ones such as Maven and Quackle. An additional goal is to give Scrabble players an excellent strategy for obtaining championship level in Spanish.
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