ORCID Identifier(s)

0000-0001-6075-5745

Graduation Semester and Year

2018

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Gergely V Záruba

Second Advisor

Manfred Huber

Abstract

The first records of wheeled seats being used for transporting disabled people date to 8th century in China, however the wheelchair has evolved tremendously since its inception. An electric-powered wheelchair, commonly called a "powerchair" is a wheelchair which incorporates batteries and electric motors into the frame, and so it can be controlled by either the user or an attendant. This control is most commonly done via a small joystick mounted on the armrest, or on the upper rear of the frame. For users who cannot manage a manual joystick, head-switches, chin-operated joysticks, sip-and-puff controllers or other custom controls may allow independent operation of the wheelchair. Although these interfaces make the wheelchair easier to operate, they do not help the user to navigate, nor do they make the user aware of the obstacles in the path of the wheelchair. In this thesis we are exploring how haptic feedback can be coupled with a short-range navigation system to make powerchairs smarter. More precisely, we employ and modify an off-the shelf haptic joystick for both getting the intended direction of motion from the user as well as providing the user with the haptic feedback in case there are obstacles that prevent the powerchair to move on its current trajectory. The smart powerchair builds and maintains a map based on obstacles that are sensed with a LIDAR (Light Detection and Ranging) using simultaneous localization and mapping (SLAM); this information is then used to provide haptic feedback and perform navigation and obstacle avoidance. The system contains custom designed hard- and firm-ware to communicate with the original wheelchair controller. The overarching custom software architecture is designed and built over ROS (The Robot Operating System).

Keywords

Haptics, Force-feedback, Semi-autonomous wheelchair, Assistive wheelchair

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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