Exploring Autonomous Mobile Robot Technologies for Indoor Cleaning: Path Planning, Obstacle Avoidance, and Sensor Integration

Abstract

Autonomous mobile robots (AMRs) are changing the way industries like logistics, healthcare, and home cleaning operate, driving efficiency while reducing the need for human labor. A major challenge for AMRs is path planning—finding the best route to navigate their environment while balancing factors like safety, energy use, and time. This task becomes even more complex in dynamic environments, where unforeseen obstacles or changing conditions can require real-time adjustments. In this review, we dive into the different path planning strategies, from global planning to local and multi-objective optimization methods. We also look at how technologies like SLAM, LiDAR, and ultrasonic sensors are helping AMRs navigate more effectively. Finally, we highlight emerging trends and discuss the key challenges that still need to be addressed to improve AMR performance and adaptability in real-world environments.