Compact RRT: A New Approach for Guided Sampling Applied to Environment Representation and Path Planning in Mobile Robotics

Abstract

In this paper it is presented a new approach to increase the dispersion of the nodes in the RRT, this approach allows a compact representation of the environment by reducing the nodes redundancy, with this, the number of samples discarded, the computational cost and the processing time of tree growth is also reduced. The developed method performs the polarization of the nodes creating search regions with the highest probability of connectivity to the tree, these regions are created from environmental discretization. Furthermore, the polarization technique presented in this paper is robust to environmental variation, not reducing its performance in more complex environments with narrow passages or long corridors. When using the Compact RRT, path planning stage is faster, because the number of nodes in the tree will be lower compared to Classic RRT.