Multiworld Motion Planning

Bobby Davis, Nicholas Sohre, Stephen J. Guy

Research output: Contribution to journalArticlepeer-review


While predictive planning approaches have had broad success in robot navigation, most implementations of them have important limitations. In particular, they plan around a single predicted outcome (plus uncertainty) or the union of several likely outcomes. Here, we introduce the multiworld motion planning problem, where a robot plans around each likely outcome separately, while maintaining a safe trajectory until it can determine which of the predictions actually happened. We introduce a method both for split detection (understanding when multiple plans can be created) and split planning (planning path over these separate contingencies). We apply our techniques to simulated robots with both holonomic and nonholonomic dynamics in a variety of scenarios. We show that our resulting approach can produce substantially safer and shorter trajectories than traditional motion planning in critical situations that commonly arise in tasks such as navigating in human environments.

Original languageEnglish (US)
Article number8417965
Pages (from-to)3968-3974
Number of pages7
JournalIEEE Robotics and Automation Letters
Issue number4
StatePublished - Oct 2018


  • Motion and path planning
  • collision avoidance
  • simulation and animation

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