Development of a Bayesian recursive algorithm to find free-spaces for an intelligent wheelchair

Area of Science:

• Robotics
• Artificial Intelligence
• Human-Computer Interaction

Background:

• Intelligent wheelchairs require advanced control systems for safe and efficient navigation.
• Shared control strategies aim to balance user input with autonomous capabilities.

Purpose of the Study:

• To develop a novel shared control strategy for intelligent wheelchairs.
• To enhance wheelchair navigation by integrating environmental sensing and user commands.

Main Methods:

• Utilized a Bayesian recursive algorithm for environmental perception and path planning.
• Integrated laser range finder data with user interface commands.
• Developed an autonomous navigation algorithm to maneuver within identified free spaces.

Main Results:

• The Bayesian recursive algorithm successfully identified the most appropriate free-space based on posterior probability.
• The autonomous navigation algorithm effectively maneuvered the wheelchair in the selected free-space.
• Experimental results confirmed excellent performance, flexibility, and fast response.

Conclusions:

• The proposed shared control strategy offers a robust solution for intelligent wheelchair navigation.
• This approach enhances user experience and safety in complex environments.
• The method demonstrates significant potential for improving assistive robotic technologies.