The Unmanned Ground Vehicle's local path plan algorithm that adapted weight according to obstacles in local area

Abstract

The existing path plan algorithms repeat process until reach to goal position (from the start position). As result of process, path plan algorithms create the optimal paths. From the algorithm point of view, created paths are optimal paths because paths are the shortest and lowest. But this path does not consider unit's moving characteristics. The current path plan algorithms have been developing that solving and supplementing the part of problems about the grid map environment. According to the passage, methods of the solving and supplementing can divide two ways. First method is path smoothing, second method is the Field D∗ algorithm. If the path smoothing is adapted in Global size (Global path in Global map), in such that case, the time constraint is not important but the optimal path will be modified. And modification of the optimal path like to has serious problems. Field D∗ algorithm is powerful path plan algorithm and this algorithm is not postprocessing like a path smoothing. And in a way it guarantees real-time path creations. But local size (local path in local map)'s real-time do not guarantee perfectly. On the basis of facts, we suggest the Unmanned Ground Vehicle (we abbreviate the word by 'UGV')'s new path plan algorithm that included UGV's moving characteristics.