Classical models of aerial swarms often describe global coordinated motion as the
combination of local interactions that happen at the individual level. Mathematically, these …

In this work, a distributed model predictive control (MPC) scheme based on consensus
theory is proposed for the formation control of a group of quadcopters. The MPC scheme …

This paper presents a novel unmanned aerial vehicle platform based on a three rotor
configuration, which can achieve the highest level of maneuverability in all 6 dimensions (ie …

In this paper, we present an online nonlinear Model Predictive Control (MPC) method for
collision-free, deadlock-free navigation by multiple autonomous nonholonomic Wheeled …

Distributed model predictive control (DMPC) is a flexible and scalable feedback control
method applicable to a wide range of systems. While the stability analysis of DMPC is quite …

In this article, a novel distributed model predictive control architecture is proposed for the
coordination and control of multivehicle formations moving within uncertain environments …

Several interesting problems in multi-robot systems can be cast in the framework of
distributed optimization. Examples include multi-robot task allocation, vehicle routing, target …

Decomposition is a fundamental principle of resolving complexity by scale, which is utilized
in a variety of decomposition-based algorithms for control and optimization. In this paper, we …

Multirobot motion planning and control has been investigated for decades and is still an
active research area due to the growing demand for both performance optimality and safety …

In this article, event‐triggered model predictive control is used for simultaneous tracking and
formation of a multi‐vehicle system with collision avoidance and obstacle avoidance. An …