Generalization of v⋆ path planning for accommodation of amortized dynamic uncertainties in plan execution

A significant generalization to the language-measure-theoretic path planning algorithm v* is presented that accounts for average dynamic uncertainties in plan execution. The planning problem thus can be solved with parametric input from the dynamics of the robotic platform under consideration. Applicability of the algorithm is demonstrated in a simulated maze solution and by experimental validation on a mobile robotic platform in the laboratory environment.