In this section
@inproceedings{Gao:2016:10.1109/IROS.2016.7759647,
author = {Gao, Y and Chang, HJ and Demiris, Y},
doi = {10.1109/IROS.2016.7759647},
publisher = {IEEE},
title = {Iterative Path Optimisation for Personalised Dressing Assistance using Vision and Force Information},
url = {http://dx.doi.org/10.1109/IROS.2016.7759647},
year = {2016}
}
TY - CPAPER
AB - We propose an online iterative path optimisationmethod to enable a Baxter humanoid robot to assist humanusers to dress. The robot searches for the optimal personaliseddressing path using vision and force sensor information: visioninformation is used to recognise the human pose and model themovement space of upper-body joints; force sensor informationis used for the robot to detect external force resistance andto locally adjust its motion. We propose a new stochastic pathoptimisation method based on adaptive moment estimation. Wefirst compare the proposed method with other path optimisationalgorithms on synthetic data. Experimental results show thatthe performance of the method achieves the smallest error withfewer iterations and less computation time. We also evaluatereal-world data by enabling the Baxter robot to assist realhuman users with their dressing.
AU - Gao,Y
AU - Chang,HJ
AU - Demiris,Y
DO - 10.1109/IROS.2016.7759647
PB - IEEE
PY - 2016///
SN - 2153-0866
TI - Iterative Path Optimisation for Personalised Dressing Assistance using Vision and Force Information
UR - http://dx.doi.org/10.1109/IROS.2016.7759647
UR - http://hdl.handle.net/10044/1/39009
ER -
