iARW: An incremental path planner algorithm based on adaptive random walks

This paper presents a new path planning algorithm that uses adaptive random walks to incrementally construct a roadmap in the robot's free configuration space. This algorithm, named Incremental Adaptive Random Walks (iARW), uses a modified version of the ARW algorithm proposed by Carpin and Pillonetto for exploring the configuration space and storing the discovered path in a roadmap. Thus, the main idea is to use bidirectional adaptive random walks to explore the configuration space but also to use and expand the roadmap whenever possible.With this approach it is possible to construct a roadmap that captures the connectivity of the free configuration space without a preprocessing phase. A comparison of our approach with other state of the art path planners illustrates the good performance of the proposed method.