Trabalho de Conclusão de Curso de Graduação
Redes neurais e algoritmos hierárquicos de pathfinding para computação de elevação e inclinação na busca de caminhos em terrenos virtuais
Fecha
2021-09-02Autor
Soares, Juliano Leonardo
Institución
Resumen
In computer games and virtual simulators, the fun, difficulty and variability of
entertainment and/or training challenges are directly related to the behavior of
characters inserted in the built virtual environments. In terms of behavior, one of the
main characteristics of these characters is the ability to move along paths that are
automatically computed. For this, pathfinding algorithms have gained greater
importance in the field of Artificial Intelligence (AI) especially when considered
together with deep neural networks (DNN). However, the integration of these AI
research areas still does not present clearly established patterns, especially when we
consider that relief information of the land used must be used in computing the cost
of the investigated paths. The objective of this TCC, therefore, is to research, develop
and test hierarchical pathfinding algorithms that consider terrain relief irregularities,
and explore DNN to optimize the search for such paths in large terrains that contain
this topographical information. With this, this work presents experiments with
traditional heuristics and DNN computed heuristics trained in the execution of the
pathfinding algorithms A∗ and HPA*, presenting a way to consider the terrain relief in
the determination of paths. From the statistical analysis of the experimental results
obtained in the TCC, it is possible to state that the use of DNN can reduce the
computational cost of both A* and HPA* considering the terrain relief.