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SUMMARY This paper introduces a novel continuous-time dynamic average consensus algorithm for networks whose interaction is described by a strongly connected and weight-balanced directed graph. The proposed distributed algorithm allows agents to track the average of their dynamic inputs with some steady-state error whose size can be controlled using a(More)
We present a novel decentralized cooperative localization algorithm for mobile robots. The proposed algorithm is a decentralized implementation of a centralized Extended Kalman Filter for cooperative localization. In this algorithm, instead of propagating cross-covariance terms, each robot propagates new intermediate local variables that can be used in an(More)
— This paper analyzes distributed algorithmic solutions to dynamic average consensus implemented in continuous time and relying on communication at discrete instants of time. Our starting point is a distributed coordination strategy that, under continuous-time communication, achieves practical asymptotic tracking of the dynamic average of the time-varying(More)
For a team of mobile robots with limited onboard resources, we propose a partially decentralized implementation of an extended Kalman filter for cooperative localization. In the proposed algorithm, unlike a fully centralized scheme that requires, at each timestep, information from the entire team to be gathered together and be processed by a single device,(More)
For a group of mobile robots with communication and computation capabilities, we consider a cooperative localization algorithm based on Unscented Kalman filtering. We present a server-client paradigm to distribute the computational cost of this algorithm among team members. The highest computational cost of the Unscented Kalamn filter comes from calculating(More)
Technological advances in ad-hoc networking and miniaturization of electro-mechanical systems are making possible the use of large numbers of mobile agents (e.g., mobile robots, human agents, unmanned vehicles) to perform surveillance, search and rescue, transport and delivery tasks in aerial, underwater, space, and land environments. However, the(More)
— We propose a distributed continuous-time algorithm to solve a network optimization problem where the global cost function is a strictly convex function composed of the sum of the local cost functions of the agents. We establish that our algorithm, when implemented over strongly connected and weight-balanced directed graph topologies, converges(More)
This paper reports a partially decentralized implementation of an Extended Kalman filter for the cooperative localization of a team of mobile robots with limited onboard resources. Unlike a fully centralized scheme that requires, at each timestep, information from the entire team to be gathered together and be processed by a single device, our algorithm(More)