{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/60100"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/60100","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Narrated guided tour following and interpretation by an autonomous wheelchair","abstract":"This work addresses the fundamental problem of how a robot acquires local knowledge about its environment. The domain that we are concerned with is a speech-commandable robotic wheelchair operating in a home/special care environment, capable of navigating autonomously to a verbally-specified location in the environment. We address this problem by incorporating a narrated guided tour following capability into the autonomous wheelchair. In our method, a human gives a narrated guided tour through the environment, while the wheelchair follows. The guide carries out a continuous dialogue with the wheelchair, describing the names of the salient locations in and around his/her immediate vicinity. The wheelchair constructs a metrical map of the environment, and based on the spatial structure and the locations of the described places, segments the map into a topological representation with corresponding tagged locations. This representation of the environment allows the wheelchair to interpret and implement high-level navigation commands issued by the user. To achieve this capability, our system consists of an autonomous wheelchair, a person- following module allowing the wheelchair to track and follow the tour guide as s/he conducts the tour, a simultaneous localization and mapping module to construct the metric gridmap, a spoken dialogue manager to acquire semantic information about the environment, a map segmentation module to bind the metrical and topological representations and to relate tagged locations to relevant nodes, and a navigation module to utilize these representations to provide speech-commandable autonomous navigation.","abstract_html":"This work addresses the fundamental problem of how a robot acquires local knowledge about its environment. The domain that we are concerned with is a speech-commandable robotic wheelchair operating in a home/special care environment, capable of navigating autonomously to a verbally-specified location in the environment. We address this problem by incorporating a narrated guided tour following capability into the autonomous wheelchair. In our method, a human gives a narrated guided tour through the environment, while the wheelchair follows. The guide carries out a continuous dialogue with the wheelchair, describing the names of the salient locations in and around his/her immediate vicinity. The wheelchair constructs a metrical map of the environment, and based on the spatial structure and the locations of the described places, segments the map into a topological representation with corresponding tagged locations. This representation of the environment allows the wheelchair to interpret and implement high-level navigation commands issued by the user. To achieve this capability, our system consists of an autonomous wheelchair, a person- following module allowing the wheelchair to track and follow the tour guide as s/he conducts the tour, a simultaneous localization and mapping module to construct the metric gridmap, a spoken dialogue manager to acquire semantic information about the environment, a map segmentation module to bind the metrical and topological representations and to relate tagged locations to relevant nodes, and a navigation module to utilize these representations to provide speech-commandable autonomous navigation.","abstract_has_math":false,"creators":["Hemachandra, Sachithra Madhawa"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Seth Teller."],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010","date_published":"2010","updated_at":"2026-07-22T22:22:13Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 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The wheelchair constructs a metrical map of the environment, and based on the spatial structure and the locations of the described places, segments the map into a topological representation with corresponding tagged locations. This representation of the environment allows the wheelchair to interpret and implement high-level navigation commands issued by the user. To achieve this capability, our system consists of an autonomous wheelchair, a person- following module allowing the wheelchair to track and follow the tour guide as s/he conducts the tour, a simultaneous localization and mapping module to construct the metric gridmap, a spoken dialogue manager to acquire semantic information about the environment, a map segmentation module to bind the metrical and topological representations and to relate tagged locations to relevant nodes, and a navigation module to utilize these representations to provide speech-commandable autonomous navigation."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Narrated guided tour following and interpretation by an autonomous wheelchair"]}]}],"canonical_facts":{"dc:contributor.advisor":["Seth Teller."],"dc:contributor.department":["Massachusetts Institute of Technology. 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The domain that we are concerned with is a speech-commandable robotic wheelchair operating in a home/special care environment, capable of navigating autonomously to a verbally-specified location in the environment. We address this problem by incorporating a narrated guided tour following capability into the autonomous wheelchair. In our method, a human gives a narrated guided tour through the environment, while the wheelchair follows. The guide carries out a continuous dialogue with the wheelchair, describing the names of the salient locations in and around his/her immediate vicinity. The wheelchair constructs a metrical map of the environment, and based on the spatial structure and the locations of the described places, segments the map into a topological representation with corresponding tagged locations. This representation of the environment allows the wheelchair to interpret and implement high-level navigation commands issued by the user. To achieve this capability, our system consists of an autonomous wheelchair, a person- following module allowing the wheelchair to track and follow the tour guide as s/he conducts the tour, a simultaneous localization and mapping module to construct the metric gridmap, a spoken dialogue manager to acquire semantic information about the environment, a map segmentation module to bind the metrical and topological representations and to relate tagged locations to relevant nodes, and a navigation module to utilize these representations to provide speech-commandable autonomous navigation."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/60100"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 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