PRISM: Pose Registration for Integrated Semantic Mapping

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

BibTeX Entry

@inproceedings{hart2018iros,
  author = {Hart, Justin W. and Shah, Rishi and Kirmani, Sean and Walker, Nick and Baldauf, Kathryn and John, Nathan and Stone, Peter},
  title = {PRISM: Pose Registration for Integrated Semantic Mapping},
  location = {Madrid, Spain},
  month = oct,
  year = {2018},
  booktitle = {2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  keywords = {semantic mapping},
  doi = {10.1109/IROS.2018.8593681},
  wwwtype = {conference},
  wwwpdf = {https://www.cs.utexas.edu/%7Epstone/Papers/bib2html-links/IROS18-hart.pdf}
}