Wheelchair driver assistance and intention prediction using POMDPs

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dc.contributor.author Taha, Tarek en_US
dc.contributor.author Valls Miro, Jaime en_US
dc.contributor.author Dissanayake, Gamini en_US
dc.contributor.editor M. Palaniswami (University of Melbourne, Australia) en_US
dc.date.accessioned 2009-11-09T05:34:29Z
dc.date.available 2009-11-09T05:34:29Z
dc.date.issued 2007 en_US
dc.identifier 2007000745 en_US
dc.identifier.citation Taha Tarek, Valls Miro Jaime, and Dissanayake Gamini 2007, 'Wheelchair driver assistance and intention prediction using POMDPs', IEEE Computer Society, Melbourne, Victoria, pp. 449-454. en_US
dc.identifier.issn 1-4244-1502-0 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/2334
dc.description.abstract Electric wheelchairs give otherwise immobile people the freedom of movement, they significantly increase independence and dramatically increase quality of life. However the physical control systems of such wheelchair can be prohibitive for some users; for example, people with severe tremors. Several assisted wheelchair platforms have been developed in the past to assist such users. Algorithms that assist specific behaviors such as door - passing, follow - corridor, or avoid - obstacles have been successful. Research has seen a move towards systems that predict the users intentions, based on the users input. These predictions have been typically limited to locations immediately surrounding the wheelchair. This paper presents a new assisted wheelchair driving system with large scale intelligent intention recognition based on POMDPs (partially observable Markov decision processes). The systems acts as an intelligent agent/decision-maker, it relies on minimal user input; to predict the users intention and then autonomously drives the user to his destination. The prediction is constantly being updated as new user input is received allowing for true user/system integration. This shifts the users focus from fine motor-skilled control to coarse control intended to convey intention. en_US
dc.publisher IEEE Computer Society en_US
dc.relation.hasversion Accepted manuscript version
dc.relation.isbasedon http://dx.doi.org/10.1109/ISSNIP.2007.4496885 en_US
dc.subject Electric wheelchairs. en
dc.subject
dc.title Wheelchair driver assistance and intention prediction using POMDPs en_US
dc.parent IEEE International Conference on Intelligent Networks, Sensor Networks and Information Processing (ISSNIP 2007) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Melbourne, Victoria en_US
dc.identifier.startpage 449 en_US
dc.identifier.endpage 454 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.conference.location Melbourne, Victoria en_US
dc.for 090200 en_US
dc.personcode 10072559 en_US
dc.personcode 040408 en_US
dc.personcode 011224 en_US
dc.percentage 100 en_US
dc.classification.name Automotive Engineering en_US
dc.classification.type FOR-08 en_US
dc.custom International Conference on Intelligent Sensors, Sensor Networks and Information Processing en_US
dc.date.activity 20071203 en_US
dc.location.activity Melbourne, Victoria en_US
dc.description.keywords Markov processes decision making decision theory handicapped aids intelligent robots medical robotics mobile robots en_US
dc.staffid 011224 en_US


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