Augmented reality control of smart wheelchair using eye-gaze–enabled selection of affordances

In this paper we present a novel augmented reality head mounted display user interface for controlling a robotic wheelchair for people with limited mobility. To lower the cognitive requirements needed to control the wheelchair, we propose integration of a smart wheelchair with an eye-tracking enabled head-mounted display. We propose a novel platform that integrates multiple user interface interaction methods for aiming at and selecting affordances derived by on-board perception capabilities such as laser-scanner readings and cameras. We demonstrate the effectiveness of the approach by evaluating our platform in two realistic scenarios: 1) Door detection, where the affordance corresponds to a Door object and the Go-Through action and 2) People detection, where the affordance corresponds to a Person and the Approach action. To the best of our knowledge, this is the first demonstration of a augmented reality head-mounted display user interface for controlling a smart wheelchair