Wheelchair Neuro Fuzzy Control and Tracking System Based on Voice Recognition

Area of Science:

• Robotics and Artificial Intelligence
• Biomedical Engineering
• Mechatronics

Background:

• Autonomous wheelchairs are crucial for enhancing mobility in individuals with disabilities.
• Advancements in computing and wireless tech enable smart wheelchair development.
• Existing solutions may lack intuitive control or sophisticated navigation.

Purpose of the Study:

• To design and implement a voice-controlled electric wheelchair.
• To integrate voice recognition and adaptive neuro-fuzzy control for enhanced user interaction.
• To improve wheelchair navigation and supervisory control via wireless sensor networks.

Main Methods:

• Utilized voice recognition algorithms for command classification.
• Implemented an adaptive neuro-fuzzy controller for real-time motor control signals.
• Integrated obstacle avoidance sensors and wireless sensor network (WSN) for tracking and control.

Main Results:

• The voice-controlled wheelchair demonstrated sophisticated control capabilities.
• The system effectively processed voice commands and sensor data for navigation.
• Experimental results validated the enhanced mobility provided by the smart wheelchair.

Conclusions:

• Combining soft-computing and mechatronics significantly advances wheelchair technology.
• The developed voice-controlled wheelchair offers improved mobility and independence for users.
• This research highlights the potential of intelligent systems in assistive devices.