Modeling and Simulation of a Sweeping Robot Based on ROS

This paper addresses the challenge of enabling sweeping robots to autonomously navigate and perform cleaning tasks independently in diverse and complex environments. Leveraging the Gazebo simulation environment, a sweeping robot is meticulously modeled as a differential drive system to realistically simulate locomotion and sensor interactions. Furthermore, sophisticated map construction and navigation algorithms are meticulously crafted within the robot operating system (ROS) framework to seamlessly facilitate exploration and cleaning operations. Through extensive experimentation and rigorous evaluation, the efficacy of the proposed approach is thoroughly demonstrated, highlighting the simulated robot’s remarkable capabilities in successful navigation and efficient cleaning. This research significantly contributes to the advancement of robotics by pioneering robust and efficient sweeping robots capable of autonomously navigating and cleaning various environments with precision and reliability. By integrating global planning algorithms into the navigation system, the robot achieves intelligent decision-making, enhancing its adaptability to complex environments and ensuring thorough cleaning coverage. The potential impact of this work transcends conventional cleaning practices, promising to revolutionize household, commercial, and industrial cleaning operations, ultimately enhancing overall efficiency, productivity, and quality of life.