Walk-behind floor scrubbers represent one of the largest and most price-sensitive segments of entry-level commercial cleaning equipment. Typically featuring a cleaning width of 400–600 mm and a 24V electrical system, they are widely used in supermarkets, retail stores, office corridors, hospital hallways, and small industrial workshops. Operated by a single user on foot, these machines typically integrate multiple electrical loads, including traction drive, brush motors, vacuum motors, water valves, and liquid level sensors. With numerous domestic manufacturers and highly fragmented control architectures, many models rely on separate, basic controllers for individual functions. Key market priorities include low system cost, ease of maintenance, moisture resistance, and simple operation. Rather than advanced intelligent features, manufacturers prioritize stable and reliable performance of essential cleaning functions.

AMR autonomous cleaning robots integrate multiple sensing technologies, including LiDAR, machine vision, ultrasonic sensors, collision detection systems, inertial measurement units (IMUs), and wheel speed encoders. They are generally available in two categories: compact indoor autonomous floor scrubbers and mid-size autonomous sweeping and scrubbing machines for industrial facilities. These robots are designed for a wide range of applications, including factories, shopping malls, hospitals, data centers, and large campuses. Their control architecture typically consists of three core units: a low-level motion controller (chassis controller), a navigation domain controller, and a cleaning system controller. Most systems adopt a distributed multi-controller architecture to coordinate navigation, vehicle motion, and cleaning operations. As one of the fastest-growing and most technically demanding segments in the cleaning equipment industry, autonomous cleaning robots offer significant market potential. However, reliable real-world deployment and adaptation to diverse operating environments remain key industry challenges.