Decentralized algorithms and architecture for tracking and identification Export

@proceedings{rao-etal-iros91, abstract = {Present two algorithms for tracking and identification in decentralized multi-sensor systems. Decentralized architectures have many benefits in terms of modularity, speed and robustness. The state estimation (tracking) algorithm is a decentralized Kalman filter (DKF) based on the extended Kalman filter. Identification is achieved by the decentralized Bayesian identification (DBI) algorithm, which identifies targets being tracked. For each of the algorithms The authors discuss optimality and the effect of reducing connectivity. The structure of the algorithms leads to the development of an architecture for a modular sensing node based on communication considerations. The authors present example implementations of both algorithms on actual transputer-based sensing nodes. They describe RCD (region of constant depth) tracking and for this develop a monopulse sonar arrangement with which they implement real-time autonomous tracking by a single sensor node. The second example implementation describes identification of targets being tracked by the DKF using the DBI on actual CCD camera-based nodes}, author = {Rao, B. S. Y. and Manyika, J. M. and Durrant-Whyte, H. F.}, booktitle = {Intelligent Robots and Systems '91. 'Intelligence for Mechanical Systems, Proceedings IROS '91. IEEE/RSJ International Workshop on}, citeulike-article-id = {3998148}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/IROS.1991.174639}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=174639}, doi = {10.1109/IROS.1991.174639}, journal = {Intelligent Robots and Systems '91. 'Intelligence for Mechanical Systems, Proceedings IROS '91. IEEE/RSJ International Workshop on}, keywords = {distributed, filtering, gaussian, inference}, pages = {1095--1100 vol.2}, posted-at = {2009-02-02 21:28:39}, priority = {2}, title = {Decentralized algorithms and architecture for tracking and identification}, url = {http://dx.doi.org/10.1109/IROS.1991.174639}, year = {1991} }

TY - CONF ID - rao-etal-iros91 L3 - citeulike-article-id:3998148 N2 - Present two algorithms for tracking and identification in decentralized multi-sensor systems. Decentralized architectures have many benefits in terms of modularity, speed and robustness. The state estimation (tracking) algorithm is a decentralized Kalman filter (DKF) based on the extended Kalman filter. Identification is achieved by the decentralized Bayesian identification (DBI) algorithm, which identifies targets being tracked. For each of the algorithms The authors discuss optimality and the effect of reducing connectivity. The structure of the algorithms leads to the development of an architecture for a modular sensing node based on communication considerations. The authors present example implementations of both algorithms on actual transputer-based sensing nodes. They describe RCD (region of constant depth) tracking and for this develop a monopulse sonar arrangement with which they implement real-time autonomous tracking by a single sensor node. The second example implementation describes identification of targets being tracked by the DKF using the DBI on actual CCD camera-based nodes JF - Intelligent Robots and Systems '91. 'Intelligence for Mechanical Systems, Proceedings IROS '91. IEEE/RSJ International Workshop on EP - 1100 vol.2 TI - Decentralized algorithms and architecture for tracking and identification T2 - Intelligent Robots and Systems '91. 'Intelligence for Mechanical Systems, Proceedings IROS '91. IEEE/RSJ International Workshop on SP - 1095 KW - distributed KW - filtering KW - gaussian KW - inference AU - Rao, BSY AU - Manyika, JM AU - Durrant-Whyte, HF PY - 1991/// UR - http://dx.doi.org/10.1109/IROS.1991.174639 ER -