Article
Model Predictive Control for Cooperative Transportation
with Feasibility-Aware Policy
Badr Elaamery
1
, Massimo Pesavento
1
, Teresa Aldovini
1
, Nicola Lissandrini
1,
* , Giulia Michieletto
2,
*
and Angelo Cenedese
1,
*
Citation: Elaamery, B.; Pesavento,
M.; Aldovini, T.; Lissandrini, N.;
Michieletto, G.; Cenedese, A. Model
Predictive Control for Cooperative
Transportation with Feasibility-
Aware Policy. Robotics 2021, 10, 84.
https://doi.org/10.3390/
robotics10030084
Academic Editor: Charalampos P.
Bechlioulis
Received: 25 May 2021
Accepted: 27 June 2021
Published: 30 June 2021
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1
Department of Information Engineering, University of Padova, 35131 Padova, Italy;
badr.elaamery@studenti.unipd.it (B.E.); massimo.pesavento@studenti.unipd.it (M.P.);
teresa.aldovini@studenti.unipd.it (T.A.)
2
Department of Management and Engineering, University of Padova, 36100 Vicenza, Italy
* Correspondence: nicola.lissandrini@phd.unipd.it (N.L.); giulia.michieletto@unipd.it (G.M.);
angelo.cenedese@unipd.it (A.C.)
Abstract:
The transportation of large payloads can be made possible with Multi-Robot Systems
(MRS) implementing cooperative strategies. In this work, we focus on the coordinated MRS trajectory
planning task exploiting a Model Predictive Control (MPC) framework addressing both the acting
robots and the transported load. In this context, the main challenge is the possible occurrence of
a temporary mismatch among agents’ actions with consequent formation errors that can cause
severe damage to the carried load. To mitigate this risk, the coordination scheme may leverage
a leader–follower approach, in which a hierarchical strategy is in place to trade-off between the
task accomplishment and the dynamics and environment constraints. Nonetheless, particularly
in narrow spaces or cluttered environments, the leader’s optimal choice may lead to trajectories
that are infeasible for the follower and the load. To this aim, we propose a feasibility-aware leader–
follower strategy, where the leader computes a reference trajectory, and the follower accounts for
its own and the load constraints; moreover, the follower is able to communicate the trajectory
infeasibility to the leader, which reacts by temporarily switching to a conservative policy. The
consistent MRS co-design is allowed by the MPC formulation, for both the leader and the follower:
here, the prediction capability of MPC is key to guarantee a correct and efficient execution of the
leader–follower coordinated action. The approach is formally stated and discussed, and a numerical
campaign is conducted to validate and assess the proposed scheme, with respect to different scenarios
with growing complexity.
Keywords:
multi-robot systems; cooperative transportation; model predictive control; leader–
follower architecture
1. Introduction
A multi-robot system (MRS) is a set of autonomous agents, able to sense the environ-
ment, take decisions, communicate information, and cooperate in order to perform goals
that are beyond the capabilities and the knowledge of each individual component [
1
]. The
strength of this architecture is indeed the possibility to accomplish complex global tasks
through the realization of simple local rules by the interacting robotic agents. An MRS
is thus mainly characterized by cooperative nature which is not altered by the addition
and/or removal of a subset of elements. In this sense, it is robust and scalable [
2
]: robust-
ness refers to the ability of a system to tolerate the failure of one or more agents, while
scalability originates from the system modularity.
Thanks to these features, in the last decade, the MRS architecture has emerged as an
effective technology in military, civil, and industrial contexts, where it is employed in a
wide range of application fields from the more traditional surveillance, monitoring, and
Robotics 2021, 10, 84. https://doi.org/10.3390/robotics10030084 https://www.mdpi.com/journal/robotics
