Cheap or Robust? The Practical Realization of Self-Driving Wheelchair Technology

TL;DR

This paper introduces a cost-effective and robust autonomous wheelchair system using commodity sensors, capable of navigating complex environments like narrow doorways, aiming for real-world adoption.

Contribution

The authors present a novel, inexpensive autonomous wheelchair platform that combines localization, mapping, and obstacle avoidance using only a commodity RGB-D sensor and wheel odometry.

Findings

Successfully navigates narrow doorways in arbitrary environments.

Uses only commodity RGB-D sensor and wheel odometry.

Generalizable software for various navigation tasks.

Abstract

To date, self-driving experimental wheelchair technologies have been either inexpensive or robust, but not both. Yet, in order to achieve real-world acceptance, both qualities are fundamentally essential. We present a unique approach to achieve inexpensive and robust autonomous and semi-autonomous assistive navigation for existing fielded wheelchairs, of which there are approximately 5 million units in Canada and United States alone. Our prototype wheelchair platform is capable of localization and mapping, as well as robust obstacle avoidance, using only a commodity RGB-D sensor and wheel odometry. As a specific example of the navigation capabilities, we focus on the single most common navigation problem: the traversal of narrow doorways in arbitrary environments. The software we have developed is generalizable to corridor following, desk docking, and other navigation tasks that are either extremely difficult or impossible for people with upper-body mobility impairments.