Ali Khalajmehrabadi, Samsung Semiconductor Inc.; Nikolaos Gatsis, Department of Electrical and Computer Engineering, University of Texas at San Antonio; Daniel Pack, Department of Electrical Engineering, The University of Tennessee at Chattanooga; David Akopian, Department of Electrical and Computer Engineering, University of Texas at San Antonio

View Abstract Sign in for premium content

Abstract:

This paper addresses the problem of anchor-free multi-agent collaborative localization. We discuss three different coarse localization schemes: 1) Intuitive Coarse Localization (ICL), 2) Multidimensional Scaling (MDS) and 3) Semidefinite Programming (SDP). Then, a unified set of sequential and parallel LS techniques are applied to modify these coarse estimates. An outlier detection procedure is also introduced for localization with the presence of outliers. The numerical comparisons yield important insights to practitioners.