2015/05/21 by Solmaz S. Kia, Kia, Solmaz S., Stephen F. Rounds +3
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Electrical engineering #Indoor and Outdoor Localization Technologies #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Systems and Control (eess.SY) #Target Tracking and Data Fusion in Sensor Networks #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1505.05908
openalex publication_date 2015/05/21 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
We consider cooperative localization technique for mobile agents with\ncommunication and computation capabilities. We start by provide and overview of\ndifferent decentralization strategies in the literature, with special focus on\nhow these algorithms maintain an account of intrinsic correlations between\nstate estimate of team members. Then, we present a novel decentralized\ncooperative localization algorithm that is a decentralized implementation of a\ncentralized Extended Kalman Filter for cooperative localization. In this\nalgorithm, instead of propagating cross-covariance terms, each agent propagates\nnew intermediate local variables that can be used in an update stage to create\nthe required propagated cross-covariance terms. Whenever there is a relative\nmeasurement in the network, the algorithm declares the agent making this\nmeasurement as the interim master. By acquiring information from the interim\nlandmark, the agent the relative measurement is taken from, the interim master\ncan calculate and broadcast a set of intermediate variables which each robot\ncan then use to update its estimates to match that of a centralized Extended\nKalman Filter for cooperative localization. Once an update is done, no further\ncommunication is needed until the next relative measurement.\n