Real-time vision-based robot localization

An algorithm for robot localization using visual landmarks is described. This algorithm determines both the correspondence between observed landmarks (in this case vertical edges in the environment) and a preloaded map, and the location of the robot from those correspondences. The primary advantages of this algorithm are its use of a single geometric tolerance to describe observation error, its ability to recognize ambiguous sets of correspondences, its ability to compute bounds on the error in localization, and its fast execution. The current version of the algorithm has been implemented and tested on a mobile robot system. In several hundred trials the algorithm has not failed, and computes location accurate to within a centimeter in less than half a second. >

Authors

• Sami Aitya
• Gregory D. Hager

Keywords

• Robot localization
• Mobile robots
• Robot kinematics
• Robot vision systems
• Robot sensing systems
• Sonar
• Cameras
• Labeling
• Computer science
• System testing
• Triangular
• Coordinate System
• Least Squares Regression
• Kalman Filter
• Focal Length
• Nonlinear Least Squares
• Figure Of Merit
• Position Error
• Local Estimates
• Error Range
• Local Problems
• Image Distortion
• Observation Error
• Structured Illumination
• Extreme Points
• Mobile Robot
• Functional Tolerance
• Static Position
• Camera Position