Driving Assistance System with Obstacle Avoidance for Electric Wheelchairs.

Area of Science:

• Robotics and Assistive Technology
• Intelligent Transportation Systems

Background:

• Manual wheelchairs lack autonomous navigation and obstacle avoidance, posing safety risks outside the user's direct line of sight.
• Existing assistive technologies may not fully address the dynamic challenges of real-world environments for wheelchair users.

Purpose of the Study:

• To develop and validate a system for converting manual wheelchairs into electric wheelchairs with enhanced safety features.
• To implement an algorithm for real-time obstacle avoidance and safe navigation tailored for wheelchair use.

Main Methods:

• Utilized the dynamic window approach (DWA) algorithm for path planning and obstacle avoidance.
• Integrated LiDAR sensors for environmental perception and real-time data acquisition.
• Developed a control system to convert manual wheelchair functionality to electric-powered, algorithm-guided operation.

Main Results:

• The system successfully demonstrated real-time obstacle avoidance capabilities.
• Testing confirmed enhanced user safety and improved wheelchair maneuverability in various scenarios.
• The algorithm effectively generated optimal paths and safe driving speeds based on sensor input.

Conclusions:

• The developed system offers a significant advancement in assistive technology for individuals with limited mobility.
• The integration of DWA and LiDAR sensors provides a robust solution for safe and autonomous wheelchair navigation.
• The system shows potential for widespread adoption, improving the independence and safety of wheelchair users.