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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 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.
@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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