Medical Autonomous Cleaning Robot Solution

Hospitals, as the frontline in infection prevention and control, have stringent requirements for environmental hygiene. However, traditional cleaning methods face multiple challenges: on one hand, the complex hospital environment and large cleaning areas result in low efficiency and high labor costs; on the other hand, inconsistent manual operations and lack of transparent supervision make standardized management difficult. Conventional cleaning struggles to meet hospital demands, creating an urgent need for automated, intelligent, and high-efficiency cleaning solutions.
To address these challenges, Esseniot introduces the Medical Autonomous Cleaning Robot Solution. This advanced cleaning robot integrates multiple cleaning modes, autonomously plans routes, and independently performs sweeping, mopping, and dust-pushing across hospital facilities. With a maximum cleaning efficiency of 1,200㎡/h, it delivers both superior cleaning performance and productivity to meet the demands of large-scale hospital environments.

System Composition




Cleaning Modes
Equipped with automatic and manual modes to accommodate different cleaning needs.
Cross Door & Elevator
Autonomously operates elevators and passes security gates for cross-floor cleaning, minimizing manual intervention.
Auto Recharging
When battery runs low, the robot auto-docks to its charger using AI vision positioning. Features 2-hour fast charging for continuous operation.
Data Visualization
Automatically generates cleaning reports with performance analytics and visualized data for efficient management.
Advantages
Precision Obstacle Avoidance
Powered by 11 high-precision sensors for accurate obstacle detection and avoidance.
High-Efficiency Cleaning
Adopts a zigzag cleaning path algorithm for optimized coverage and faster operation.
Smart Inspection
Pre-set inspection routes, automatic garbage detection and cleaning. Alerts staff for large items
Cost Reduction
Cuts labor costs by 50%+ vs manual cleaning, Reduces management workload through automation