Robot Path Planning in Uncertain Environments: A Language-Measure-Theoretic Approach

Devesh K. Jha, Yue Li, Thomas A. Wettergren, Asok Ray

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


This paper addresses the problem of goal-directed robot path planning in the presence of uncertainties that are induced by bounded environmental disturbances and actuation errors. The offline infinite-horizon optimal plan is locally updated by online finite-horizon adaptive replanning upon observation of unexpected events (e.g., detection of unanticipated obstacles). The underlying theory is developed as an extension of a grid-based path planning algorithm, called ν ∗, which was formulated in the framework of probabilistic finite state automata (PFSA) and language measure from a control-theoretic perspective. The proposed concept has been validated on a simulation test bed that is constructed upon a model of typical autonomous underwater vehicles (AUVs) in the presence of uncertainties.

Original languageEnglish (US)
Article number034503
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Issue number3
StatePublished - Mar 1 2015

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications


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