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PRISM: Pose Registration for Integrated Semantic Mapping.
Justin W. Hart,
Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter
Stone.
In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
October 2018.
Many robotics applications involve navigating to positions specified in terms oftheir semantic significance. A robot operating in a hotel may need to deliverroom service to a named room. In a hospital, it may need to deliver medicationto a patient's room. The Building-Wide Intelligence Project at UT Austin hasbeen developing a fleet of autonomous mobile robots, called BWIBots, whichperform tasks in the computer science department. Tasks include guiding aperson, delivering a message, or bringing an object to a location such as anoffice, lecture hall, or classroom. The process of constructing a map that arobot can use for navigation has been simplified by modern SLAM algorithms. Theattachment of semantics to map data, however, remains a tedious manual processof labeling locations in otherwise automatically generated maps. This paperintroduces a system called PRISM to automate a step in this process by enablinga robot to localize door signs -- a semantic markup intended to aid the humanoccupants of a building -- and to annotate these locations in its map.
@InProceedings{IROS18-hart,
author = {Justin W. Hart and Rishi Shah and Sean Kirmani and Nick Walker and Kathryn Baldauf and Nathan John and Peter Stone},
title = {PRISM: Pose Registration for Integrated Semantic Mapping},
booktitle = {Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
location = {Madrid, Spain},
month = {October},
year = {2018},
abstract = {
Many robotics applications involve navigating to positions specified in terms of
their semantic significance. A robot operating in a hotel may need to deliver
room service to a named room. In a hospital, it may need to deliver medication
to a patient's room. The Building-Wide Intelligence Project at UT Austin has
been developing a fleet of autonomous mobile robots, called BWIBots, which
perform tasks in the computer science department. Tasks include guiding a
person, delivering a message, or bringing an object to a location such as an
office, lecture hall, or classroom. The process of constructing a map that a
robot can use for navigation has been simplified by modern SLAM algorithms. The
attachment of semantics to map data, however, remains a tedious manual process
of labeling locations in otherwise automatically generated maps. This paper
introduces a system called PRISM to automate a step in this process by enabling
a robot to localize door signs -- a semantic markup intended to aid the human
occupants of a building -- and to annotate these locations in its map.
},
}
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