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

Devesh K. Jha | Zendy; Yue Li | Zendy; Thomas A. Wettergren | Zendy; Asok Ray | Zendy

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

Author(s) -

Devesh K. Jha,

Yue Li,

Thomas A. Wettergren,

Asok Ray

Publication year - 2014

Publication title -

journal of dynamic systems measurement and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.528

H-Index - 89

eISSN - 1528-9028

pISSN - 0022-0434

DOI - 10.1115/1.4027876

Subject(s) - motion planning , measure (data warehouse) , occupancy grid mapping , computer science , path (computing) , robot , probabilistic logic , grid , perspective (graphical) , automaton , bounded function , mobile robot , time horizon , mathematical optimization , plan (archaeology) , finite state machine , artificial intelligence , algorithm , mathematics , data mining , history , mathematical analysis , geometry , archaeology , programming language

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 m?, 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. [DOI: 10.1115/1.4027876

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