An Intelligent Path Planning System for Robot Navigation in an Unknown Environment

Abstract

In this paper, a novel approach to solve the mobile robot path planning problem in an unknown environment is presented. Inherently, the obstacle information from robot perception is contaminated with uncertainties, and thus, the acquired obstacle knowledge for path planning needs to be updated dynamically. Therefore, the development of an adaptive path planning scheme capable of determining a desired path with uncertain, and incomplete obstacle knowledge is necessary. We use the concept of traversability vectors to analyze the spatial-relations between the robot and obstacles in the task environment. Then, these analyzed relations are used to determine the obstacles that must be bypassed by the robot, and the ways to bypass them. Dynamically changing obstacle knowledge can be accommodated by replanning the path at the time when a change is reported. The proposed scheme can work very efficiently since because of the elimination of an exhausted search process that is often required in previous approaches. We implement a computer program to simulated the proposed planning scheme. A graphical representation for robot motions guided by the planned paths is illustrated to show the feature of the presented work.