Real-Time Globally Optimized Path Planning in a Dynamic Environment

Abstract

This paper presents a novel method for optimal path planning in a dynamic environment. This method employs fuzzy logic to establish a model of the environment and the ant colony system (ACS) algorithm to search for the shortest and collision-free route. The result of the computer simulation shows that the method introduced in this paper is effective, and can be applied to any dynamic environment for real-time globally optimized path planning of mobile robots.