Obstacle Avoidance of Multi-Sensor Intelligent Robot Based on Road Sign Detection

Area of Science:

• Robotics
• Artificial Intelligence
• Sensor Fusion

Background:

• Existing ultrasonic obstacle avoidance robots have limitations in following dynamic information and avoiding specific hazards like potholes.
• Current autonomous mobile robots often lack integrated strategies for diverse environmental challenges.

Purpose of the Study:

• To propose an intelligent obstacle avoidance system for autonomous mobile robots using multi-sensor fusion.
• To enhance robot navigation capabilities by incorporating visual information for road sign recognition and infrared sensing for pothole detection.

Main Methods:

• Implemented a CascadeClassifier for road sign detection and recognition.
• Utilized multi-sensor information fusion (ultrasonic, infrared, camera) for path planning and obstacle avoidance logic.
• Developed an integrated system processing sensor data via a microprocessor for control command output.

Main Results:

• The system successfully integrates ultrasonic, infrared, and visual data for comprehensive environmental perception.
• Demonstrated the robot's ability to avoid obstacles, recognize road signs, and detect ground depressions (potholes).
• Experimental validation confirmed the feasibility of the multi-sensor approach in a complex, manually constructed environment.

Conclusions:

• The proposed multi-sensor fusion system significantly improves autonomous mobile robot obstacle avoidance capabilities.
• Integrating visual and infrared sensing addresses limitations of traditional ultrasonic-only systems, enabling navigation in more challenging terrains.
• This design offers a robust solution for intelligent obstacle avoidance in dynamic and complex environments.