Cell-RRT: Decomposing the environment for better plan

In order to define an architecture for task and motion planning of a mobile robot, we propose the Cell-RRT path planner that combines the advantages of planning approaches by decomposition of the environment and the advantages of probabilistic approaches. Experiments of the method for various decomposition granularities and various adjustments of the planner settings show that using a bias towards the goal while choosing a random configuration reduces the paths length but can cause failures, that the choice of the criterion for analysing the environment is important, and that the method can profit from a reuse of already made computations in a part of the environment.