User recognition for guiding and following people with a mobile robot in a clinical environment
Markus Eisenbach, Alexander Vorndran, Sven Sorge, Horst-Michael Gross
Abstract
Rehabilitative follow-up care is important for stroke patients to regain their motor and cognitive skills. We aim to develop a robotic rehabilitation assistant for walking exercises in late stages of rehabilitation. The robotic rehab assistant is to accompany inpatients during their self-training, practicing both mobility and spatial orientation skills. To hold contact to the patient, even after temporally full occlusions, robust user re-identification is essential. Therefore, we implemented a person re-identification module that continuously re-identifies the patient, using only few amount of the robot's processing resources. It is robust to varying illumination and occlusions. State-of-the-art performance is confirmed on a standard benchmark dataset, as well as on a recorded scenario-specific dataset. Additionally, the benefit of using a visual re-identification component is verified by live-tests with the robot in a stroke rehab clinic.
BibTeX
@inproceedings{iros2015_userrecognitionf,
title = {User recognition for guiding and following people with a mobile robot in a clinical environment},
author = {Markus Eisenbach and Alexander Vorndran and Sven Sorge and Horst-Michael Gross},
booktitle = {IROS 2015},
year = {2015}
}