Decentralized Control of Uncertain Multi-Agent Systems with Connectivity Maintenance and Collision Avoidance

This paper addresses the problem of navigation control of a general class of uncertain nonlinear multi-agent systems in a bounded workspace of $\mathbb{R}^n$ with static obstacles. In particular, we propose a decentralized control protocol such that each agent reaches a predefined position at the workspace, while using only local information based on a limited sensing radius. The proposed scheme guarantees that the initially connected agents remain always connected. In addition, by introducing certain distance constraints, we guarantee inter-agent collision avoidance, as well as, collision avoidance with the obstacles and the boundary of the workspace. The proposed controllers employ a class of Decentralized Nonlinear Model Predictive Controllers (DNMPC) under the presence of disturbances and uncertainties. Finally, simulation results verify the validity of the proposed framework.Comment: IEEE European Control Conference (ECC), Limassol, Cyprus, June 201

Event-triggered coordination for formation tracking control in constrained space with limited communication

In this paper, the formation tracking control is studied for a multi-agent system (MAS) with communication limitations. The objective is to control a group of agents to track a desired trajectory while maintaining a given formation in non omniscient constrained space. The role switching triggered by the detection of unexpected spatial constraints facilitates efficiency of event-triggered control in communication bandwidth, energy consumption and processor usage. A coordination mechanism is proposed based on a novel role ‘coordinator’ to indirectly spread environmental information among the whole communication network and form a feedback link from followers to the leader to guarantee the formation keeping. A formation scaling factor is introduced to scale up or scale down the given formation size in the case that the region is impassable for MAS with the original formation size. Controllers for the leader and followers are designed and the adaptation law is developed for the formation scaling factor. The conditions for asymptotic stability of MAS are discussed based on the Lyapunov theory. Simulation results are presented to illustrate the performance of proposed approaches

Event-Triggered Multi-Lane Fusion Control for 2-D Vehicle Platoon Systems with Distance Constraints

This paper investigates the event-triggered fixedtime multi-lane fusion control for vehicle platoon systems with distance keeping constraints where the vehicles are spread in multiple lanes. To realize the fusion of vehicles in different lanes, the vehicle platoon systems are firstly constructed with respect to a two-dimensional (2-D) plane. In case of the collision and loss of effective communication, the distance constraints for each vehicle are guaranteed by a barrier function-based control strategy. In contrast to the existing results regarding the command filter techniques, the proposed distance keeping controller can constrain the distance tracking error directly and the error generated by the command filter is coped with by adaptive fuzzy control technique. Moreover, to offset the impacts of the unknown system dynamics and the external disturbances, an unknown input reconstruction method with asymptotic convergence is developed by utilizing the interval observer technique. Finally, two relative threshold triggering mechanisms are utilized in the proposed fixed-time multi-lane fusion controller design so as to reduce the communication burden. The corresponding simulation results also verify the effectiveness of the proposed strategy

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas

A Review of Consensus-based Multi-agent UAV Applications

In this paper, a review of distributed control for multi-agent systems is proposed, focusing on consensus-based applications. Both rotary-wing and fixed-wing Unmanned Aerial Vehicles (UAVs) are considered. On one side, methodologies and implementations based on collision and obstacle avoidance through consensus are analyzed for multirotor UAVs. On the other hand, a target tracking through consensus is considered for fixed-wing UAVs. This novel approach to classify the literature could help researchers to assess the outcomes achieved in these two directions in view of potential practical implementations of consensus-based methodologies