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

Gillham, Michael, Howells, Gareth, Spurgeon, Sarah K., Kelly, Stephen W., Pepper, Matthew G. (2013) Real-time Doorway Detection and Alignment Determination for Improved Trajectory Generation in Assistive Mobile Robotic Wheelchairs. In: Proceedings of Fourth International Conference on Emerging Security Technologies (EST). . pp. 62-65.

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.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: robotic wheelchair; doorway approach angle; pattern recognition; assistive system; real-time; door passing
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7882.P3 Pattern Recognition
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7895.E42 Embedded Systems
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Image and Information Engineering
Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: M. Gillham
Date Deposited: 01 Feb 2014 20:47 UTC
Last Modified: 29 May 2019 11:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/38138 (The current URI for this page, for reference purposes)
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