Iterative Temporal Planning in Uncertain Environments With Partial Satisfaction Guarantees

Morteza Lahijanian, Matthew R. Maly, Dror Fried, Lydia E. Kavraki, Hadas Kress-Gazit, Moshe Y. Vardi

Research output: Contribution to journalArticlepeer-review

Abstract

This paper introduces a motion-planning framework for a hybrid system with general continuous dynamics to satisfy a temporal logic specification consisting of cosafety and safety components in a partially unknown environment. The framework employs a multilayered synergistic planner to generate trajectories that satisfy the specification and adopt an iterative replanning strategy to deal with unknown obstacles. When the discovery of an obstacle renders the specification unsatisfiable, a division between the constraints in the specification is considered. The cosafety component of the specification is treated as a soft constraint, whose partial satisfaction is allowed, while the safety component is viewed as a hard constraint, whose violation is forbidden. To partially satisfy the cosafety component, inspirations are taken from indoor-robotic scenarios, and three types of (unexpressed) restrictions on the ordering of subtasks in the specification are considered. For each type, a partial satisfaction method is introduced, which guarantees the generation of trajectories that do not violate the safety constraints while attending to partially satisfying the cosafety requirements with respect to the chosen restriction type. The efficacy of the framework is illustrated through case studies on a hybrid car-like robot in an office environment.

Original languageEnglish
Article number7469409
Pages (from-to)583-599
Number of pages17
JournalIEEE Transactions on Robotics
Volume32
Issue number3
DOIs
StatePublished - Jun 2016
Externally publishedYes

Keywords

  • Control synthesis
  • formal methods
  • hybrid systems
  • motion planning
  • partial satisfaction
  • temporal logic

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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