Efficient Room Plan Navigation for Robot Vacuum Cleaner Using vSLAM Algorithms

Abstract

This research paper focuses on Complete Coverage Path Planning (CCPP) for robot vacuum cleaners utilizing Visual Simultaneous Localization and Mapping (vSLAM) algorithms. The study addresses the challenge of optimizing coverage path planning while considering the limited battery capacities of robot vacuum cleaners, aiming to reduce energy consumption. The utilization of vSLAM algorithms for map building is emphasized due to their advantages over other sensors in providing more accurate and detailed environmental information. The research involves the implementation and comparison of various CCPP algorithms to identify the most efficient and effective method for complete area coverage. Additionally, an innovative approach is proposed, combining an off-line algorithm with an online strategy, tailored for robot vacuum cleaners with limited prior knowledge of the environment. By relying solely on the camera's field of view, this approach aims to achieve complete coverage while considering real-world constraints. Furthermore, the paper explores the impact of varying camera visual angles on algorithm performance, documenting the implications of different camera perspectives on the coverage path planning efficiency.