<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gurtner, Martin</style></author><author><style face="normal" font="default" size="100%">Jiří Zemánek</style></author><author><style face="normal" font="default" size="100%">Zdeněk Hurák</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Alternating direction method of multipliers-based distributed control for distributed manipulation by shaping physical force fields</style></title><secondary-title><style face="normal" font="default" size="100%">The International Journal of Robotics Research</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">February</style></date></pub-dates></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-size: 16px; caret-color: rgb(51, 51, 51); color: rgb(51, 51, 51); font-family: &amp;quot;Open Sans&amp;quot;, sans-serif;&quot;&gt;This paper proposes an algorithm for decomposing and possibly distributing an optimization problem that naturally emerges in distributed manipulation by shaping physical force fields through actuators distributed in space (arrays of actuators). One or several manipulated objects located in this field can “feel the force” and move simultaneously and independently. The control system has to produce commands for all actuators so that desired forces are developed at several prescribed places. This can be formulated as an optimization problem that has to be solved in every sampling period. Exploiting the structure of the optimization problem is crucial for platforms with many actuators and many manipulated objects, hence the goal of decomposing the huge optimization problem into several subproblems. Furthermore, if the platform is composed of interconnected actuator modules with computational capabilities, the decomposition can give guidance for the distribution of the computation to the modules. We propose an algorithm for decomposing/distributing the optimization problem using Alternating Direction Method of Multipliers (ADMM). The proposed algorithm is shown to converge to modest accuracy for various distributed platforms in a few iterations. We demonstrate our algorithm through numerical experiments corresponding to three physical experimental platforms for distributed manipulation using electric, magnetic, and pressure fields. Furthermore, we deploy and test it on real experimental platforms for distributed manipulation using an array of solenoids and ultrasonic transducers.&lt;/span&gt;&lt;/p&gt;
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