A mapmaking robot integrates accumulated sensor data into a data structure that can be used for future localization or planning operations. Localization is the process of determining the robot's location within its environment. This paper describes experiments in which a robot simultaneously makes a map and localizes to that map. The map is a collection of tangent vectors constructed from stored sonar readings localized to a series of estimated poses. The vectors retain sensed surface normal information to improve accuracy. The localization scheme is a Hough transform into a space described by the robot's current sonar scan. The Hough transform finds a best fit in the presence of both sporadic sensor noise and discretization error.
|Movie, 4:30, Quicktime with Sorenson codec, max 250 kb/s (42MB)||mapmaking-movie-5.250kbit.mov|
|Movie, 4:30, Quicktime with Sorenson codec, max 100 kb/s (26MB)||mapmaking-movie-5.100kbit.mov|
|PostScript version of the final ICRA paper (8.1 MB)||proceedings version|
|PostScript version of the submitted ICRA paper||submitted version|
HTML version of the submitted ICRA paper
This HTML document represents the submitted version of the paper (August, 1999). The version printed in the proceedings includes our results with more experiments, including using the algorithm to determine orientation. The figures on this page correspond to those in the newer version of the paper, however, and are clearer for being in color. Figure 7 on this page also includes an animated GIF version showing more frames of the sequence.