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

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 $3$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

Potential Fields for Maintaining Connectivity of Mobile Networks

The control of mobile networks of multiple agents raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In this paper, we consider the problem of controlling a network of agents so that the resulting motion always preserves the connectivity property of the network. In particular, the connectivity condition is translated to differentiable constraints on individual agent motion by considering the dynamics of the Laplacian matrix and its spectral properties. Artificial potential fields are then used to drive the agents to configurations away from the undesired space of disconnected networks while avoiding collisions with each other. We conclude by illustrating a class of interesting problems that can be achieved while preserving connectivity constraints

Finite-time Motion Planning of Multi-agent Systems with Collision Avoidance

Finite-time motion planning with collision avoidance is a challenging issue in multi-agent systems. This paper proposes a novel distributed controller based on a new Lyapunov barrier function which guarantees finite-time stability for multi-agent systems without collisions. First, the problem of finite-time motion planning of multi-agent systems is formulated. Then, a novel finite-time distributed controller is developed based on a Lyapunov barrier function. Finally, numerical simulations demonstrate the effectiveness of proposed method

Distributed Obstacle Avoidance-Formation Control of Mobile Robotic Network with Coordinated Group Stabilization

We present a distributed control law for a group of agents that solves the problem of formation control with obstacle avoidance and that can be combined with a coordinated group stabilization control law. In particular, we consider a control law that is given by a linear combination of distributed formation, distributed obstacle avoidance and centralized group motion control laws. Simulation results show the effectiveness of our proposed control law

Error Analysis in Multi-Agent Control Systems

Any cooperative control scheme relies on some measurements which are often assumed to be exact to simplify the analysis. However, it is known that in practice all measured quantities are subject to error, which can deteriorate the overall performance of the network significantly. This work proposes a new measurement error analysis in the control of multi-agent systems. In particular, the connectivity preservation of multi-agent systems with state-dependent error in distance measurements is considered. It is assumed that upper bounds on the measurement error and its rate of change are available. A general class of distributed control strategies is then proposed for the distance-dependent connectivity preservation of the agents in the network. It is shown that if two neighboring agents are initially located in the connectivity range, they are guaranteed to remain connected at all times. Furthermore, the formation control problem for a team of single-integrator agents subject to distance measurement error is investigated using navigation functions. Collision, obstacle and boundary avoidance are important features of the proposed strategy. Conditions on the magnitude of the measurement error and its rate of change are derived under which a new error-dependent formation can be achieved anywhere in the space. The effectiveness of the proposed control strategies in consensus and containment problems is demonstrated by simulation