Robust adaptive motion planning in the presence of dynamic obstacles
Nurali Virani, Minghui Zhu · 2016
Usually in game theoretic formulations for robust motion planning, the model as well as the capabilities (input set) of all dynamic obstacles are assumed to be known. This paper aims to relax the assumption of known input set by proposing a unified framework for motion planning and admissible input set estimation. The proposed approach models every dynamic obstacle as an uncertain-constrained system and then uses the uncertainty estimation technique to estimate the bounds of those uncertainties. The RRT* algorithm with uncertainty estimation for robust adaptive motion planning in presence of dynamic obstacles is presented in this paper. Simulation examples have been used to validate the proposed algorithm.