Optimization of Path Planning for Domestic Sweeping Robots Using Fuzzy PID Control

Abstract

This paper explores the development of an advanced path optimization method for household sweeping robots, enhancing their operational efficiency and accuracy in diverse and complex environments. With the proliferation of smart home devices, the demand for autonomous cleaning robots that can navigate and clean efficiently across various household layouts has significantly increased. Traditional path planning algorithms often fall short in dynamically changing and cluttered domestic spaces, leading to suboptimal cleaning paths and missed areas. To address these challenges, we introduce a fuzzy PID control approach, integrated with a multi-sensor data regulation system. This innovative method employs fuzzy logic to handle the uncertainty and variability inherent in real-world environments, while the PID control optimizes the robot's movements for precision and responsiveness. The integration of fuzzy logic allows for adaptive threshold setting, which enhances the robot's ability to make real-time decisions based on the continuous feedback from its array of sensors. This paper presents a detailed analysis of the fuzzy PID algorithm's performance in navigating complex paths, demonstrating significant improvements in path efficiency and obstacle avoidance compared to conventional methods. By conducting extensive simulations and real-world tests in various household settings, we establish the robustness and reliability of our proposed model. The results highlight the potential of fuzzy PID control to revolutionize the navigation capabilities of domestic robots, making them more adaptable and efficient in complex environments. This research not only contributes to the field of robotics but also opens new avenues for the application of fuzzy logic in smart home technologies.