  In this paper, we propose and evaluate a novel human-machine interface (HMI)
for controlling a standing mobility vehicle or person carrier robot, aiming for
a hands-free control through upper-body natural postures derived from gaze
tracking while walking. We target users with lower-body impairment with
remaining upper-body motion capabilities. The developed HMI bases on a sensing
array for capturing body postures; an intent recognition algorithm for
continuous mapping of body motions to robot control space; and a personalizing
system for multiple body sizes and shapes. We performed two user studies:
first, an analysis of the required body muscles involved in navigating with the
proposed control; and second, an assessment of the HMI compared with a standard
joystick through quantitative and qualitative metrics in a narrow circuit task.
We concluded that the main user control contribution comes from Rectus
Abdominis and Erector Spinae muscle groups at different levels. Finally, the
comparative study showed that a joystick still outperforms the proposed HMI in
usability perceptions and controllability metrics, however, the smoothness of
user control was similar in jerk and fluency. Moreover, users' perceptions
showed that hands-free control made it more anthropomorphic, animated, and even
safer.
