Year: 2025
Type: article
Abstract: In this paper, we address the problem of cooperative manipulation of a cable-suspended load by a team of aerial robots. Unlike classical approaches that rely on centralized controllers, we propose aDistributed Nonlinear Model Predictive Control(DNMPC) framework in which the UAVs communicate over a peer-to-peer network a reduced amount of variables. In the proposed method, each robot handles only a small subset of the global optimization problem. The optimal motion computed by the DNMPC loop is then used as a reference for local nonlinear controllers that track the trajectory and compute the robot's actuation inputs. We validate the proposed scheme both through numerical simulations and real-world experiments on theFly-Cranesystem: a rigid platform connected to three robots by pairs of cables.
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4413887016