Marco Baracca, Andre Meixner, Giuseppe Averta, Paolo Salaris, Tamin Asfour and Matteo Bianchi
Proceedings of IEEE11th International Conference on Automation, Robotics, and Applications (ICARA)
Abstract
Dual-arm manipulation is a key enabler for significantly enhancing the interaction between humans and robots, and their capabilities to purposefully shape the surrounding environment. However, the spatiotemporal coordination between the motion of the hands required for this type of actions makes their planning not trivial. A proper definition of these coordination patterns moving from the human example could simplify their translation on the robot side, fostering the generation of effective bimanual tasks. In this work, we propose Multivariate functional Principal Component Analysis (MfPCA) as a mathematical tool to encode inter-hands temporal kinematic covariations in terms of principal spatiotemporal coordination patterns in the Cartesian domain. We compared these patterns extracted from a dataset of human bimanual tasks with those resulting from the usage of classical fPCA, applied independently to each hand (univariate fPCA). We found that MfPCA allows for a better classification of the tasks, with respect to a state of the art taxonomy. For what concerns motion planning, MfPCA and fPCA yield similar accuracy in the reconstruction of the motion, but with a smaller number of principal components needed in the MfPCA case. These results, although preliminary, can open interesting perspectives for the usage of MfPCA for human-like bimanual motion planning and control of robotic manipulators, as well as for action recognition, to enable a more effective human-robot interaction.
@INPROCEEDINGS{10977603,
author={Baracca, Marco and Meixner, Andre and Averta, Giuseppe and Salaris, Paolo and Asfour, Tamim and Bianchi, Matteo},
booktitle={2025 11th International Conference on Automation, Robotics, and Applications (ICARA)},
title={A Multivariate Functional Analysis of Inter-Hands Spatiotemporal Coordination in Human Bimanual Tasks and its Implications for Robotics},
year={2025},
volume={},
number={},
pages={140-144},
keywords={Hands;Translation;Shape;Robot kinematics;Taxonomy;Human-robot interaction;Functional analysis;Planning;Spatiotemporal phenomena;Principal component analysis;bimanual manipulation;functional analysis;multivariate functional principal component analysis;human motion;planning and control;human-robot interaction},
doi={10.1109/ICARA64554.2025.10977603}}