Real-Time Pathfinding in Unknown Terrain via Reconnection with an Ideal Tree

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8864)


In real-time pathfinding in unknown terrain an agent is required to solve a pathfinding problem by alternating a time-bounded deliberation phase with an action execution phase. Real-time heuristic search algorithms are designed for general search applications with time constraints but unfortunately in pathfinding they are known to produce poor-quality solutions. In this paper we propose \(\mathrm{p-FRIT }_\mathrm{{RT}}\), a real-time version of FRIT, a recently proposed algorithm able to produce very good-quality solutions in pathfinding under strict, but not fully real-time constraints. The idea underlying \(\mathrm{p-FRIT }_\mathrm{{RT}}\) draws inspiration from bug algorithms, a family of pathfinding algorithms. Yet, as we show, \(\mathrm{p-FRIT }_\mathrm{{RT}}\) is able to outperform a well-known bug algorithm and is able to solve graph search problems that are more general than pathfinding. \(\mathrm{p-FRIT }_\mathrm{{RT}}\) also outperforms significantly—generating solutions six times shorter when time constraints are tight—a previously proposed real-time version of FRIT and the real-time heuristic search algorithm that is considered to have state-of-the-art performance in real-time pathfinding.




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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nicolás Rivera
    • 1
  • León Illanes
    • 2
  • Jorge A. Baier
    • 2
  1. 1.Department of InformaticsKing’s College LondonLondonUK
  2. 2.Departmento de Ciencia de la ComputaciónPontificia Universidad Católica de ChileSantiagoChile

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