Decentralized Delayed-State Information Filter (DDSIF): A new approach for cooperative decentralized tracking

  • Authors:

  • J. Capitán;L. Merino;F. Caballero;A. Ollero

  • Affiliations:

  • University of Seville, Camino de los Descubrimientos s/n, 41092, Sevilla, Spain;School of Engineering, Pablo de Olavide University, Carretera Utrera km1, 41013, Sevilla, Spain;University of Seville, Camino de los Descubrimientos s/n, 41092, Sevilla, Spain;University of Seville, Camino de los Descubrimientos s/n, 41092, Sevilla, Spain and Center for Advanced Aerospace Technology (CATEC), Seville, Spain

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2011

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Abstract

This paper presents a decentralized data fusion approach to perform cooperative perception with data gathered from heterogeneous sensors, which can be static or carried by robots. In particular, a decentralized delayed-state information filter (DDSIF) is described, in which full-state trajectories (that is, delayed states) are considered to fuse the information. This approach allows obtaining an estimation equal to that provided by a centralized system and reduces the impact of communication delays and latency in the estimation. The sparseness of the information matrix maintains the communication overhead at a reasonable level. The method is applied to cooperative tracking, and some results in disaster management scenarios are shown. In this kind of scenario, the target might move in both open-field and indoor areas, so the fusion of data provided by heterogeneous sensors is beneficial. The paper also shows experimental results with real data and integrating several sources of information.