A Novel Probabilistic Path Planning Method in Periodic Dynamic Environments

Saeed Toosizadeh and Seyyed Mohammad R. Farshchi


Path planning, Robot planning, Dynamic environment, Probabilistic planning


In this paper we proposed a novel path planning method for a special class of dynamic environments, namely periodic environments, in which the motions of the moving obstacles are periodic. We show that for these kinds of environments, many problems are inherent to planning in dynamic environments disappear. For repetitive environments it is possible to generate a roadmap in a pre-processing stage, which can be used multiple times to quickly solve individual planning queries. This is in contrast to general dynamic environments, whose transitoriness invalidates the premise that a pre-processed roadmap can be used multiple times. Simulation result shown that the proposed approach is suitable and applicable for any robot with any number of degrees of freedom in two and three dimensional workspaces.

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