RRT-Edge: A compact approach for path planning of mobile robots

Abstract

In this article, a new method is presented in order to increase node dispersion on RRTs. This approach allows for a better environment representation, reducing the amount of nodes in the tree. The proposed RRT differs from Classic RRT by an insertion of a new node-tree connection method. The proposed affixing rule uses a tree whose edges are of variable length, which more rapidly explores the environment's structure. In order to reduce edges overlapping and the amount of nodes, new nodes could be added along the edges, instead of only outside of them. Furthermore, this work proposes a discrete density metric which will be used to compare, by simulation experiments, the classic method to the technique here presented. This technique generates improvements on the uniformity of the tree's expansion and on the graph's exploration speed in the path-planning phase. The results obtained suggest a reduction of up to 70% of the node amount, while keeping a constant density.