Constraint Programming for Path Planning with Uncertainty

Solving the Optimal Search Path Problem
  • Michael Morin
  • Anika-Pascale Papillon
  • Irène Abi-Zeid
  • François Laviolette
  • Claude-Guy Quimper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7514)


The optimal search path (OSP) problem is a single-sided detection search problem where the location and the detectability of a moving object are uncertain. A solution to this \(\mathcal{NP}\)-hard problem is a path on a graph that maximizes the probability of finding an object that moves according to a known motion model. We developed constraint programming models to solve this probabilistic path planning problem for a single indivisible searcher. These models include a simple but powerful branching heuristic as well as strong filtering constraints. We present our experimentation and compare our results with existing results in the literature. The OSP problem is particularly interesting in that it generalizes to various probabilistic search problems such as intruder detection, malicious code identification, search and rescue, and surveillance.


Path Planning Motion Model Constraint Programming Malicious Code Incumbent Solution 
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-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Michael Morin
    • 1
  • Anika-Pascale Papillon
    • 2
  • Irène Abi-Zeid
    • 3
  • François Laviolette
    • 1
  • Claude-Guy Quimper
    • 1
  1. 1.Department of Computer Science and Software EngineeringUniversité LavalQuébecCanada
  2. 2.Department of Mathematics and StatisticsUniversité LavalQuébecCanada
  3. 3.Department of Operations and Decision SystemsUniversité LavalQuébecCanada

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