Yutian Mao

Flocking with obstacle avoidance and connectivity maintenance in multi-agent systems

The problems of flocking with both connectivity maintenance and obstacle avoidance for the network of dynamic agents are addressed. In the case where the initial network is connected, a set of decentralized flocking control protocols is presented by utilizing artificial potential functions combined with stream functions to enable the group to asymptotically achieve the desired stable flocking motion, which could not only maintain the network connectivity of the dynamic multi-agent systems for all time but also make all the agents avoid obstacles smoothly without trapping into local minima. Finally, nontrivial simulations and experiments are worked out to verify the effectiveness of the theoretical methods.

Distributed tracking for networked Euler-Lagrange systems without velocity measurements

The problem of distributed coordinated tracking control for networked Euler-Lagrange systems without velocity measurements is investigated. Under the condition that only a portion of the followers have access to the leader, sliding mode estimators are developed to estimate the states of the dynamic leader in finite time. To cope with the absence of velocity measurements, the distributed observers which only use position information are designed. Based on the outputs of the estimators and observers, distributed tracking control laws are proposed such that all the followers with parameter uncertainties can track the dynamic leader under a directed graph containing a spanning tree. It is shown that the distributed observer-controller guarantees asymptotical stability of the closed-loop system. Numerical simulations are worked out to illustrate the effectiveness of the control laws.

Distributed flocking of second-order multi-agent systems with global connectivity maintenance

This paper investigates the problem of connectivity-preserving flocking of multiple autonomous agents with second-order dynamics. First, the inverse power iteration algorithm is formulated in a completely distributed manner to estimate the algebraic connectivity, i.e., the second smallest eigenvalue of the group Laplacian, as well as the corresponding eigenvector. Furthermore, distributed gradient-based flocking algorithms that exploit decentralized eigenvalue/eigenvector estimation are developed both to steer the agent group to the desired flocking motion and to maintain the global connectivity of the underlying network during maneuvers. Different from the common potential/tension function method which keeps certain fixed edges all the time, the algorithm proposed in this paper guarantees the global connectivity which allows any existing edge to be broken, thus gives more freedom of motions for the agents. Finally, nontrivial simulations are performed to demonstrate the correctness and effectiveness of the theoretical results.

Distributed flocking of lagrangian systems with global connectivity maintenance

Distributed control strategies with connectivity maintenance are proposed for addressing connected flocking of a team of lagrangian systems. First, a completely distributed estimation strategy is devised for estimating the algebraic connectivity, i.e., the second smallest eigenvalue of graph Laplacian, as well as the corresponding eigenvector. Furthermore, based on the estimated parameters, a cooperative flocking algorithm is developed which could steer the agents to the desired flocking motion and to keep the algebraic connectivity to be bounded below by a positive number, which guarantees global network connectivity preservation during maneuvers. Different from the local connectivity maintenance method which keeps some fixed edges for all time, the proposed algorithm guarantees the connectivity while allowing any existing edge to be broken, which enhances the flexibility and adaptability for the overall system. Finally, nontrivial simulation results are presented to show the effectiveness of the proposed control algorithm.

Flocking of multi-robot systems with connectivity maintenance on directed graphs

Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields (APF) which could guarantee the connectivity maintenance, collision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved, and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that all robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.

Distributed Motion Coordination for Multi-Agent Systems with Connectivity Maintenance Using Backbone-Based Networks

Abstract This paper addresses the problem of distributed connectivity constrained motion coordination of multiple autonomous mobile agents. Different from traditional flat network structure which lacks flexibility and scalability when performing complex spatially distributed tasks, a novel distributed framework for construction of backbone-based hierarchical communication networks is proposed. Firstly, the proposed method periodically extracts a subset of agents which can form the communication backbone from the original network using only local information, thus partitions the system into backbone agents and non-backbone agents. Furthermore, the global network connectivity of the system is maintained at two levels: connectivity-preserving potential functions are used to maintain existing links in the backbone; connectivity between backbone and non-backbone agents is achieved via a leader-follower formation control scheme with backbone agents as the leaders. Finally, nontrivial numerical simulations are worked out to verify the theoretical results.

Rendezvous of nonholonomic multiple unicycles with connectivity maintenance

In this paper, the problem of distributed rendezvous of a network of multiple unicycles with nonholonomic kinematics is investigated. In contrast to traditional artificial potential field (APF) based approaches, decentralized and bounded time-varying continuous control protocols are developed via devising a class of smooth and bounded navigation functions which is free of local minima and nicely integrates consensus requirement, connectivity maintenance and collision avoidance, simultaneously. It is shown that the proposed bounded controllers could enable the group to converge to the common position with a common orientation while preserving the network connectivity during the system evolution if the underlying network is initially connected. Finally, simulations are conducted to verify the effectiveness of the proposed control algorithms.

Distributed adaptive tracking on Lagrangian systems with reduced interaction

In this paper, we propose a distributed adaptive approach for tracking problem without using leaders velocity information, where agents are modeled by Euler-Lagrange equations. It is assumed that only a small fraction of agents within the leaders communication range are informed about the position of the leader. Without using the leaders velocity information, a connectivity-preserving adaptive controller is proposed to achieve tracking control on Lagrangian systems with the leader of constant velocity. Moreover, position and velocity consensus can be achieved asymptotically with the proposed control strategy. Numerical simulations are further provided to illustrate the theoretical results.