Dynamic Programming Inspired Global Optimal Path Planning for Mobile Robots

Abstract

Optimal path planning for mobile robots can improve the output in a warehouse and therefore have the potential to greatly increase the profit of a warehouse. Dynamic programming has long been used for optimal path planning tasks. Different from most works in this research area, which use dynamic programming with grid discretization to approximate the global optimal solution, in this paper, we propose an efficient dynamic programming inspired global optimal path planning solution for the continuous state space. The proposed algorithm can find the exact global optimal solution or the shortest path to the goal position from any starting point in the map.