A hybrid system for multi-goal navigation and map building of an autonomous vehicle in unknown environments

A solution by hybrid algorithms is proposed in this paper for real-time map building and navigation for multiple goals purpose. In real world applications, an intelligent mobile vehicle is required to reach multiple goals with a shortest path that, in this paper, is capable of being implemented in TSP (Traveling Salesman Problem) by a Genetic Algorithm (GA) with minimized overall distance. A D*-Lite-based algorithm is applied to generate path while a mobile vehicle explores through a terrain and builds a map in unknown environments. After the global path is planned, it creates a breadcrumb trail leading to the multiple goals. A LIDAR-based local navigation algorithm is employed to plan a collision-free path along breadcrumbs. In this paper, simulation and experimental results demonstrate that the real-time concurrent map building and multi-goal navigation of an autonomous vehicle is successfully performed under unknown environments.