Smelting Networks For Real Time Cooperative Planning In The Presence Of Uncertainties
S. S. Iyengar, Sandeep Gulati, J. Barhen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1988
This paper discusses the applicability and limitations of the conventional knowledge representations and Al paradigms in designing algorithms for multi-sensor fusion for the uncertainty prone multiple target tracking (MTT) problem. A knowledge-based framework for solution to this problem necessitates developing mechansims for efficient online knowledge acquisition and exploration of alternate knowledge representations as the existing structures prove inadequate in this context. In this paper we describe the use of Smelting Networks for knowledge acquisition, target state representation, resolution of sensor ambiguities and environmental uncertainties. These networks are drawn from a biological cooperative phenomenon and used to enrapture situational constraints, determine track-to-target associations and avoid generation of redundant associations for trajectory estimation.