Hierarchical path-finding for Navigation Meshes (HNA*)

Path-finding can become an important bottleneck as both the size of the virtual environments and the number of agents navigating them increase. It is important to develop techniques that can be efficiently applied to any environment independently of its abstract representation. In this paper we present a hierarchical NavMesh representation to speed up path-finding. Hierarchical path-finding (HPA*) has been successfully applied to regular grids, but there is a need to extend the benefits of this method to polygonal navigation meshes. As opposed to regular grids, navigation meshes offer representations with higher accuracy regarding the underlying geometry, while containing a smaller number of cells. Therefore, we present a bottom-up method to create a hierarchical representation based on a multilevel k-way partitioning algorithm (MLkP), annotated with sub-paths that can be accessed online by our Hierarchical NavMesh Path-finding algorithm (HNA*). The algorithm benefits from searching in graphs with a much smaller number of cells, thus performing up to 7.7 times faster than traditional A¿ over the initial NavMesh. We present results of HNA* over a variety of scenarios and discuss the benefits of the algorithm together with areas for improvement.Peer ReviewedPostprint (author's final draft

Performance Issues And Gains Of Caching The Pathfinding Data

Using non-cached methods for finding the shortest path between nodes is the most common case when using pathfinding systems. That approach generates a couple of issues. Foremost, it has a significant impact on processing resources as calculations must be done over again for each iteration, even for the repeating events. That’s not a big concern if pathfinding is invoked a reasonable number of times or the nodes involved are always different, but if pathfinding occurs many times on the same nodes, then the caching of once calculated path becomes an acceptable course of action. This paper has explored one of such caching algorithms, FAST-N algorithm and compared it with standard non-cached pathfinding. Doing so, it outlined margins of justifiable use of such systems. On a small number of pathfinding requests or simple node structure, because of increase in memory usage and rather hefty initial calculation processing requirements, it has been concluded that non-cached system makes more sense than cached one. On the other hand, when confronted with a large number of pathfinding requests and more complex node structure, caching can generate significant benefits concerning processing power and speed

Pathfinding in Games

Commercial games can be an excellent testbed to artificial intelligence (AI) research, being a middle ground between synthetic, highly abstracted academic benchmarks, and more intricate problems from real life. Among the many AI techniques and problems relevant to games, such as learning, planning, and natural language processing, pathfinding stands out as one of the most common applications of AI research to games. In this document we survey recent work in pathfinding in games. Then we identify some challenges and potential directions for future work. This chapter summarizes the discussions held in the pathfinding workgroup

Inteligencia artificial en tiempo real: razonamiento rebatible en juegos estratégicos digitales

Los Sistemas de Inteligencia Artificial en Tiempo Real son sistemas que interactúan en forma continua con el entorno, tratan con información incompleta, gestionan eventos sincrónicos y asincrónicos y garantizan respuestas en tiempos establecidos. En esta línea de investigación se estudia la aplicación de sistemas de razonamiento rebatible a juegos estratégicos, principalmente aquellos digitales con buen grado de interactividad como los de simulación en tiempo real.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Inteligencia artificial en tiempo real: razonamiento rebatible en juegos estratégicos digitales

Los Sistemas de Inteligencia Artificial en Tiempo Real son sistemas que interactúan en forma continua con el entorno, tratan con información incompleta, gestionan eventos sincrónicos y asincrónicos y garantizan respuestas en tiempos establecidos. En esta línea de investigación se estudia la aplicación de sistemas de razonamiento rebatible a juegos estratégicos, principalmente aquellos digitales con buen grado de interactividad como los de simulación en tiempo real.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Generation of navigation graphs for indoor space

This article proposes a comprehensive approach to computing a navigation graph for an indoor space. It focuses on a single floor, but the work is easily extensible to multi-level spaces. The approach proceeds by using a formal model, based on the combinatorial map but enhanced with geometric and semantic information. The process is almost fully automatic, taking as input the building plans providing the geometric structure of the floors and semantics of the building, such as functions of interior spaces, portals, etc. One of the novel aspects in this work was the use of combinatorial maps and their duals to provide a compact formal description of the topology and connectivity of the indoor structure represented by a connected, embedded graph. While making use of existing libraries for the more routine computational geometry involved, the research develops several new algorithms, including one for computing the local kernel of a region. The process is evaluated by means of a case study using part of a university building