Hierarchical Scenarios for Behavior Planning in Autonomous Robots

Sekou A. K. Diane, Sergey V. Manko, Ilan D. Margolin, Alexey K. Novoselskiy · 2019

Task scheduling and behavior planning are important components for enabling robot autonomy in a number of applied problems. This paper provides a methodology for straightforward description and automatic formation of scenarios that lead a robot or a multi-robot system to a successful completion of a given complex task. We employ a finite-automata approach to definition of individual tasks within the scenario, which as a whole is represented by an oriented graph. A multilevel scenario formation is described for simplification of the traveling salesman problem and for scene analysis in the problem of demolition debris removal. The input of the proposed algorithm is a weakly structured sensory data. The produced output contains the hierarchical scenario in the form of a recursively nested graph.

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