Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies
Name
2005.03153.pdf
Description
Accepted version
Size
5.95 MB
Format
Adobe PDF
Checksum (MD5)
35f20e287a25236dee012492cc61ddc1
Author(s)
Culbertson, Preston
Slotine, Jean-Jacques
Schwager, Mac
Date Issued
2021
Journal
IEEE Transactions on Robotics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Culbertson, Preston, Slotine, Jean-Jacques and Schwager, Mac. 2021. "Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies." IEEE Transactions on Robotics, 37 (6).
Version
Author's final manuscript
Abstract
In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in SE(3) . The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller’s behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller’s performance using numerical simulations of a manipulation task in 3-D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/TRO.2021.3072021
