<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Robotic wheelchairs should move among humans without bringing about uncomfortable situation to them. This paper tackles this issue to propose a method of navigation in indoor environments with presence of humans based on the observation of head information obtained from color and range images. Initially head regions in the color image are tracked and their orientations are estimated using AdaBoost based particle filter trained to classify multiple-pose faces. Then the head orientation data are integrated with the head position data in the range image to determine the wheelchair motion so that it can smoothly move among humans. Experimental results demonstrate the feasibility of the proposed approach</p></abstract>

Robotic wheelchairs should move among humans without bringing about uncomfortable situation to them. This paper tackles this issue to propose a method of navigation in indoor environments with presence of humans based on the observation of head information obtained from color and range images. Initially head regions in the color image are tracked and their orientations are estimated using AdaBoost based particle filter trained to classify multiple-pose faces. Then the head orientation data are integrated with the head position data in the range image to determine the wheelchair motion so that it can smoothly move among humans. Experimental results demonstrate the feasibility of the proposed approach

Socially Acceptable Smart Wheelchair Navigation From Head Orientation Observation

Faculty of Electrical & Electronic Engineering, University Tun Hussein Onn Malaysia (UTHM)

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Robotic wheelchairs should move among humans without bringing about uncomfortable situation to them. This paper tackles this issue to propose a method of...

Socially Acceptable Smart Wheelchair Navigation From Head Orientation Observation

Publié en ligne: 27 déc. 2017

Pages: 630 - 643

Reçu: 28 févr. 2014

Accepté: 01 juin 2014

DOI: https://doi.org/10.21307/ijssis-2017-673

Mots clés
Smart wheelchair navigation, human-shared environment, head-tracking

© 2014 Razali Tomari et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Socially Acceptable Smart Wheelchair Navigation From Head Orientation Observation

Publié en ligne: 27 déc. 2017

Pages: 630 - 643

Reçu: 28 févr. 2014

Accepté: 01 juin 2014

DOI: https://doi.org/10.21307/ijssis-2017-673

Mots clésSmart wheelchair navigation, human-shared environment, head-tracking

© 2014 Razali Tomari et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Smart wheelchair navigation, human-shared environment, head-tracking