High-Efficiency Automatic Recharging Mechanism for Cleaning Robot Using Multi-Sensor

Area of Science:

• Robotics
• Artificial Intelligence
• Sensor Fusion

Background:

• Cleaning robots are prevalent service robots with high market penetration.
• Efficient autonomous recharging is crucial for maintaining continuous operation of cleaning robots.
• Current recharging methods may lack the speed and accuracy required for intelligent systems.

Purpose of the Study:

• To develop a high-efficiency mechanism for intelligent cleaning robots to automatically return to charging when power is low.
• To improve the speed and reliability of the autonomous recharging process.
• To address challenges like location estimation and angle errors during the return-to-charge maneuver.

Main Methods:

• Combines motor encoder data with neural network linear regression for robot self-localization.
• Utilizes a self-rotating camera to detect infrared spots from the docking station for precise location.
• Employs a two-stage infrared detection system (existing and extended range).
• Integrates six-axis acceleration and ultrasound sensors to correct angle errors caused by collisions.

Main Results:

• The proposed mechanism enables intelligent cleaning robots to return to charging efficiently and quickly.
• Accurate robot self-localization and docking station identification were achieved.
• Error correction using acceleration and ultrasound sensors proved effective against collision-induced angle deviations.
• Experimental results demonstrated a significant improvement in recharging efficiency.

Conclusions:

• The developed autonomous recharging mechanism significantly enhances the operational efficiency of cleaning robots.
• Sensor fusion and advanced algorithms enable robust and rapid return-to-charge functionality.
• This technology is vital for improving the performance and user experience of service robots.