PRISM: Pose Registration for Integrated Semantic Mapping

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.

Authors

• Justin W. Hart
• Rishi Shah
• Sean Kirmani
• Nick Walker 0001
• Kathryn Baldauf
• Nathan John
• Peter Stone 0001

Keywords

• Robots
• Semantics
• Three-dimensional displays
• Cameras
• Two dimensional displays
• Computational modeling
• Navigation
• Semantic Map
• Manual Process
• Simultaneous Localization And Mapping
• Automated Guided Vehicles
• Department Of Computer Science
• Cost Function
• Visual System
• Tetragonal
• Nonlinear Programming
• Pose Estimation
• Null Space
• Map Construction
• Rigid Transformation
• Signage
• Automatic Annotation
• Human Operator
• Image Correction
• 2D Space
• Camera Calibration
• Robot Navigation
• Semantic Annotation
• Text Extraction
• Homogeneous Coordinates
• Navigation Map
• Pipeline Stages
• Computer Vision
• 3D Pose