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2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
This paper presents a probabilistic framework for scene modeling and active perception planning in complex environments. It tackles the problems of representing detection and transition uncertainties in multi-object scenes without knowledge of the total number of objects in the scenario. The correct association of observation data with scene information is essential for reasonable incorporation of sequencing measurements into the scene model. This work also deals with the probabilisticdoi:10.1109/aim.2009.5229779 fatcat:i47objekpng2laq2danvaan53q