ResearchSpace

Multi-agent target tracking using particle filters enhanced with context data

Show simple item record

dc.contributor.author Claessens, R
dc.contributor.author De Waal, A
dc.contributor.author De Villiers, P
dc.contributor.author Penders, A
dc.contributor.author Pavlin, G
dc.contributor.author Tuyls, K
dc.date.accessioned 2016-10-13T13:40:18Z
dc.date.available 2016-10-13T13:40:18Z
dc.date.issued 2015-05
dc.identifier.citation Claessens, R., De Waal. A., De Villers, P. Penders, A, Pavlin, G. and Tuyls, K. 2015. Multi-agent target tracking using particle filters enhanced with context data. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multi-agent Systems, Istanbul, 4-8 May 2015, pp 1933-1934. en_US
dc.identifier.uri http://www.aamas2015.com/en/AAMAS_2015_USB/aamas/p1933.pdf
dc.identifier.uri http://hdl.handle.net/10204/8828
dc.description Proceedings of the 2015 International Conference on Autonomous Agents and Multi-agent Systems, Istanbul, 4-8 May 2015. . Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. en_US
dc.description.abstract The proposed framework for Multi-Agent Target Tracking supports i) tracking of objects and ii) search and rescue based on the fusion of very heterogeneous data. The system is based on a novel approach to fusing sensory observations, intelligence and context data (i.e. the data about the environmental conditions relevant for the tracked target). In contrast to the traditional approaches to target tracking (e.g. maritime or aviation domains), the emphasis is on tracking with low quality data sampled at low frequencies from different sensors dispersed throughout a larger area that may be only partially covered. In this demo we illustrate a live, real-time target tracking application that uses a Multi-Agent System approach to find and connect relevant information sources. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Worklist;16106
dc.subject Distributed information fusion en_US
dc.subject Bayesian networks en_US
dc.subject Particle filters en_US
dc.subject Target tracking en_US
dc.subject Situation & threat assessment en_US
dc.title Multi-agent target tracking using particle filters enhanced with context data en_US
dc.type Other Material en_US
dc.identifier.apacitation Claessens, R., De Waal, A., De Villiers, P., Penders, A., Pavlin, G., & Tuyls, K. 2015. <i>Multi-agent target tracking using particle filters enhanced with context data.</i> http://hdl.handle.net/10204/8828 en_ZA
dc.identifier.chicagocitation Claessens, R, A De Waal, P De Villiers, A Penders, G Pavlin, and K Tuyls. 2015. <i>Multi-agent target tracking using particle filters enhanced with context data.</i> http://hdl.handle.net/10204/8828 en_ZA
dc.identifier.vancouvercitation Claessens R, De Waal A, De Villiers P, Penders A, Pavlin G, Tuyls K. 2015. <i>Multi-agent target tracking using particle filters enhanced with context data.</i> http://hdl.handle.net/10204/8828 en_ZA
dc.identifier.ris TY - Other Material AU - Claessens, R AU - De Waal, A AU - De Villiers, P AU - Penders, A AU - Pavlin, G AU - Tuyls, K AB - The proposed framework for Multi-Agent Target Tracking supports i) tracking of objects and ii) search and rescue based on the fusion of very heterogeneous data. The system is based on a novel approach to fusing sensory observations, intelligence and context data (i.e. the data about the environmental conditions relevant for the tracked target). In contrast to the traditional approaches to target tracking (e.g. maritime or aviation domains), the emphasis is on tracking with low quality data sampled at low frequencies from different sensors dispersed throughout a larger area that may be only partially covered. In this demo we illustrate a live, real-time target tracking application that uses a Multi-Agent System approach to find and connect relevant information sources. DA - 2015-05 DB - ResearchSpace DP - CSIR KW - Distributed information fusion KW - Bayesian networks KW - Particle filters KW - Target tracking KW - Situation & threat assessment LK - https://researchspace.csir.co.za PY - 2015 T1 - Multi-agent target tracking using particle filters enhanced with context data TI - Multi-agent target tracking using particle filters enhanced with context data UR - http://hdl.handle.net/10204/8828 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record