A Frontier-Based Coverage Path Planning Algorithm for Robot Exploration in Unknown Environment

Abstract

This paper presents a path planning algorithm for robot exploration in unknown large-scale environments. The proposed algorithm employs a finite state machine to iteratively derive the action that the robot takes to explore its environment when no prior map is available. The finite state machine contains two states, that is zigzag state and travel state. In the zigzag state, the robot explores the current cell using a zigzag pattern and adds frontier nodes. In the travel state, the robot moves to another cell by going to the nearest frontier node. Compared with previous studies, the proposed algorithm can realize complete exploration while maintaining efficiency. Simulation results demonstrate that the efficiency and robustness of the proposed algorithm for exploring the unknown large-scale environments as compared with two other state-of-art algorithms.