Various applications require networked agents to cooperatively achieve specified formations. In this paper, formation reconfiguration for a group of identical agents with limited communication capabilities is considered. Since the agents considered are identical, their roles are interchangeable, and each position in the desired formation can be taken by any agent. To reduce the total amount of node movement required for formation reconfiguration, a weighted graph matching based node mapping strategy is developed to specify the node correspondence between an arbitrary initial graph and the desired graph. After the node mapping is determined, agents are required to move physically to form the desired formation. Since agents are only able to communicate within a certain range, formation reconfiguration must be accomplished with network connectivity constraints (i.e., specified nodes remain within specified sensing and communication ranges). A decentralized control scheme is developed to guarantee network connectivity by maintaining a desired neighborhood determined by the node mapping algorithm, and to ensure convergence of all agents to the desired configuration with collision avoidance among agents. The developed strategy is demonstrated through simulation results.
Systems of networked mobile robots, such as unmanned aerial or ground vehicles, will play important roles in future military and commercial applications. The communications for such systems will typically be over wireless links and may require that the robots form an ad hoc network and communicate on a peer-to-peer basis. In this paper, we consider the problem of optimizing the network topology to minimize the total traffic in a network required to support a given set of data flows under constraints on the amount of movement possible at each mobile robot. In this paper, we consider a subclass of this problem in which the initial and final topologies are trees, and the movement restrictions are given in terms of the number of edges in the graph that must be traversed. We develop algorithms to optimize the network topology while maintaining network connectivity during the topology reconfiguration process. Our topology reconfiguration algorithm uses the concept of prefix labelling and routing to move nodes through the network while maintaining network connectivity. We develop two algorithms to determine the final network topology: an optimal, but computationally complex algorithm, and a greedy suboptimal algorithm that has much lower complexity. We present simulation results to compare the performance of these algorithm.
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