3,353 research outputs found
Position and Orientation Based Formation Control of Multiple Rigid Bodies with Collision Avoidance and Connectivity Maintenance
This paper addresses the problem of position- and orientation-based formation
control of a class of second-order nonlinear multi-agent systems in a D
workspace with obstacles. More specifically, we design a decentralized control
protocol such that each agent achieves a predefined geometric formation with
its initial neighbors, while using local information based on a limited sensing
radius. The latter implies that 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 novel class of potential functions
and do not require a priori knowledge of the dynamical model, except for
gravity-related terms. Finally, simulation results verify the validity of the
proposed framework
Decentralized formation control with connectivity maintenance and collision avoidance under limited and intermittent sensing
A decentralized switched controller is developed for dynamic agents to
perform global formation configuration convergence while maintaining network
connectivity and avoiding collision within agents and between stationary
obstacles, using only local feedback under limited and intermittent sensing.
Due to the intermittent sensing, constant position feedback may not be
available for agents all the time. Intermittent sensing can also lead to a
disconnected network or collisions between agents. Using a navigation function
framework, a decentralized switched controller is developed to navigate the
agents to the desired positions while ensuring network maintenance and
collision avoidance.Comment: 8 pages, 2 figures, submitted to ACC 201
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
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
Almost Global Asymptotic Formation Stabilization Using Navigation Functions
We present a navigation function through which a group of mobile agents can be coordinated to achieve a particular formation, both in terms of shape and orientation, while avoiding collisions between themselves and with obstacles in the environment. Convergence is global and complete, subject to the constraints of the navigation function methodology. Algebraic graph theoretic properties associated with the interconnection graph are shown to affect the shape of the navigation function. The approach is centralized but the potential function is constructed in a way that facilitates complete decentralization. The strategy presented will also serve as a point of reference and comparison in quantifying the cost of decentralization in terms of performance
Task-driven multi-formation control for coordinated UAV/UGV ISR missions
The report describes the development of a theoretical framework for coordination and control of combined teams of UAVs and UGVs for coordinated ISR missions. We consider the mission as a composition of an ordered sequence of subtasks, each to be performed by a different team. We design continuous cooperative controllers that enable each team to perform a given subtask and we develop a discrete strategy for interleaving the action of teams on different subtasks. The overall multi-agent coordination architecture is captured by a hybrid automaton, stability is studied using Lyapunov tools, and performance is evaluated through numerical simulations
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