Multi-Sensor Intelligent Robot designed for Mentally Challenged

Abstract

The proposed intelligent obstacle avoidance design of an autonomous mobile robot based on multi-sensor information fusion seems to address the limitations of existing ultrasonic-based obstacle avoidance systems by incorporating visual information from road signs and adding an infrared ranging sensor for avoiding pits. Overall, this design aims to enhance obstacle avoidance capabilities by integrating visual information from road signs and incorporating an infrared ranging sensor. By fusing data from multiple sensors and employing intelligent logic, the robot can autonomously navigate through a multi-obstruction environment, avoiding obstacles and pits effectively. This model involves Road Sign Detection, Multi-Sensor Information Fusion, Path Planning, Obstacle Avoidance Logic, Control System, and Feasibility Verification. The design's feasibility is verified through analysis and experimentation. The acquired distances from the ultrasonic sensor and infrared distance measuring sensors are analysed to ensure they provide accurate and reliable information. Additionally, the trained road sign detection model is evaluated to assess its performance. Finally, experiments are conducted in manually constructed complex environments to validate the effectiveness of the proposed design.