A distributed approach to human multi-robot physical interaction. Lippi, M., Marino, A., & Chiaverini, S. 2019. ![A distributed approach to human multi-robot physical interaction [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex In this paper, a distributed scheme to allow a human operator to physically interact with a multi-manipulator system is devised. Manipulators are tightly connected to a rigid object and a human operator interacts with it to perform, for example, a cooperative transportation task. The strategy foresees two layers. The top layer is in charge of assigning a compliant behaviour to the object through an admittance model whose reference trajectory is dynamically adjusted to regulate the human-object interaction force. Moreover, since the parameters of the dynamic model of the human arm end-point are supposed to be time-varying and completely unknowns with unknown bounds, a robust adaptive control is envisaged in this layer. The output of this layer is a desired object trajectory which is tracked by the bottom layer. In detail, the latter resorts to a robust adaptive control strategy to both track the object trajectory and control the internal stresses exerted by the manipulators on the object which unavoidably arise due to dynamic and kinematic uncertainties and synchronization errors. Simulations involving a setup with three dual-arm Movo mobile robots corroborate the theoretical findings. © 2019 IEEE.
@conference{
11580_74345,
author = {Lippi, Martina and Marino, Alessandro and Chiaverini, Stefano},
title = {A distributed approach to human multi-robot physical interaction},
year = {2019},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
volume = {2019-October},
booktitle = {2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)},
abstract = {In this paper, a distributed scheme to allow a human operator to physically interact with a multi-manipulator system is devised. Manipulators are tightly connected to a rigid object and a human operator interacts with it to perform, for example, a cooperative transportation task. The strategy foresees two layers. The top layer is in charge of assigning a compliant behaviour to the object through an admittance model whose reference trajectory is dynamically adjusted to regulate the human-object interaction force. Moreover, since the parameters of the dynamic model of the human arm end-point are supposed to be time-varying and completely unknowns with unknown bounds, a robust adaptive control is envisaged in this layer. The output of this layer is a desired object trajectory which is tracked by the bottom layer. In detail, the latter resorts to a robust adaptive control strategy to both track the object trajectory and control the internal stresses exerted by the manipulators on the object which unavoidably arise due to dynamic and kinematic uncertainties and synchronization errors. Simulations involving a setup with three dual-arm Movo mobile robots corroborate the theoretical findings. © 2019 IEEE.},
keywords = {Adaptive control systems; Manipulators; Personnel; Trajectories, Cooperative transportation; Distributed approaches; Human-object interaction; Kinematic uncertainty; Physical interactions; Reference trajectories; Robust-adaptive control; Synchronization error, Human robot interaction},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076726216&doi=10.1109/SMC.2019.8914468&partnerID=40&md5=03016ba95f9d90d0cdad4d49a8e235b5},
doi = {10.1109/SMC.2019.8914468},
isbn = {9781728145693},
pages = {728--734}
}
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