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

  • Nicolás Rivera
  • León Illanes
  • Jorge A. Baier
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.


Goal State Search Problem Ideal Tree Search Graph Clockwise Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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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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