Boumediene MouadMehennaoui LamineLachouri Abderazzak2024-05-212024-05-212022-02-09VOLUME 15, N° 3 2021http://dspace.univ-skikda.dz:4000/handle/123456789/1804Square grid representations of the state‐space are a com‐ monly used tool in path planning. With applications in a variety of disciplines, including robotics, computatio‐ nal biology, game development, and beyond. However, in large‐scale and/or high dimensional environments the creation and manipulation of such structures become too expensive, especially in applications when an accurate re‐ presentation is needed. In this paper, we present a method for reducing the cost of single‐query grid‐based path planning, by focu‐ sing the search to a smaller subset, that contains the optimal solution. This subset is represented by a hyper‐ rectangle, the location, and dimensions of which are cal‐ culated departing from an initial feasible path found by a fast search using the RRT* algorithm. We also present an implementation of this focused discretization method cal‐ led FDA*, a resolution optimal algorithm, where the A* algorithm is employed in searching the resulting graph for an optimal solution. We also demonstrate through si‐ mulation results, that the FDA* algorithm uses less me‐ mory and has a shorter run‐time compared to the classic A* and thus other graph‐based planning algorithms, and at the same time, the resulting path cost is less than that of regular RRT based algorithms.enArticle