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Real-Time Doorway Detection and Alignment Determination for Improved Trajectory Generation in Assistive Mobile Robotic Wheelchairs

Michael Gillham, Gareth Howells, Sarah K. Spurgeon, Stephen W. Kelly, Matthew Pepper

Year
2013
Citations
12

Abstract

Powered wheelchair users may find operation in enclosed environments such as buildings difficult, a fundamental problem exists: wheelchairs are not much narrower than the doorway they wish to pass through. The ability to detect and pass through doorways represents a major current challenge for automated guided wheelchairs. We utilize a simple doorway pattern recognition technique for fast processing in a real-time system for robotic wheelchair users. We are able to show a 96% detection and identification of 5 individual doorways and an 86% recognition rate of 22 separate approach angles and translations. We conclude that pattern recognition using features obtained from simple constrained infrared ranging sensor data binning can be utilized for fast identification of doorways, and important coarse position and approach angle determination, suitable for real-time trajectory adjustment, representing a significant enhancement in this area.

Keywords

Computer scienceTrajectoryWheelchairComputer visionIdentification (biology)Artificial intelligenceMobile robotPosition (finance)Mobile deviceRobot

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