Incremental Contingency Planning for Recovering from Uncertain Outcomes

  • Yolanda E-MartínEmail author
  • María D. R-Moreno
  • David E. Smith
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9868)


Incremental Contingency Planning is a framework that considers all potential failures in a plan and attempts to avoid them by incrementally adding contingency branches to the plan in order to improve the overall probability. The planner focuses its attempts on the higher probability outcomes. Precautionary planning is a form of incremental contingency planning that takes advantage of the speed of replanning for easy contingencies and only considers the unrecoverable outcomes in the plan. In this work, we present an approach to incrementally generating contingency branches to deal with uncertain outcomes. The main idea is to first generate a high probability non-branching seed plan, which is then augmented with contingency branches to handle the most critical outcomes. Any remaining outcomes are handled by runtime replanning.


Plan Graph Plan Solution Alternative Outcome Interaction Information Successful Round 
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.



This work was supported by the NASA Safe Autonomous Systems Operations (SASO) project, the MINECO project EphemeCH TIN2014-56494-C4-4-P, and UAH project 2015/00297/001.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Yolanda E-Martín
    • 1
    Email author
  • María D. R-Moreno
    • 2
  • David E. Smith
    • 3
  1. 1.Centre for Automation and RoboticsCSIC-UPMMadridSpain
  2. 2.Universidad de AlcaláMadridSpain
  3. 3.NASA Ames Research CenterMoffett FieldUSA

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