Distributed NMPC for Cooperative Aerial Manipulation of Cable-Suspended Loads

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 a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Distributed Nonlinear Model Predictive Control</i> (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 the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Fly-Crane</i> system: a rigid platform connected to three robots by pairs of cables.