Language measure-theoretic path planning in the presence of dynamic obstacles
作者： Siddharth Sonti , Nurali Virani , Devesh K. Jha , Kushal Mukherjee , Asok Ray
关键词: Measure (physics) 、 Probabilistic automaton 、 Motion planning 、 Any-angle path planning 、 Stochastic modelling 、 Mathematics 、 Finite-state machine 、 Stochastic process 、 Mathematical optimization 、 Path (graph theory)
摘要: The paper presents an algorithm to solve goal-directed path planning problems in dynamic and uncertain environments. A grid-based algorithm, called ν*, was formulated the framework of probabilistic finite state automata (PFSA) from a control-theoretic perspective. work reported this extends formulation environments with static obstacles include presence stochastic motion models. problem involves initial plan that is based on time-averaged likelihood being present at particular location. This information inferred model. Additionally, there re-planning component, current measurements. Results numerical simulation are presented demonstrate efficacy proposed concept.
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