Technical University of Munich

@inproceedings{hanek_vision-based_2000,
 author = {R Hanek and T Schmitt},
 title = {Vision-Based Localization and Data Fusion in a System of Cooperating
	Mobile Robots},
 booktitle = {Proc. of the {IEEE} Intl. Conf. on Intelligent Robots and Systems},
 year = {2000},
 pages = {1199–1204},
 publisher = {{IEEE/RSJ}},
 abstract = {The approach presented in this paper allows a team of mobile robots
	to estimate cooperatively their poses, i.e. positions and orientations,
	and the poses of other observed objects from images. The images are
	obtained by calibrated color cameras mounted on the robots. Model
	knowledge of the robots' environment, the geometry of observed objects,
	and the characteristics of the cameras are represented in curve functions
	which describe the relation between model curves in the image and
	the sought pose parameters. The pose parameters are estimated by
	minimizing the distance between model curves and actual image curves.
	Observations from possibly different view points obtained at different
	times are fused by a method similar to the extended Kalman filter.
	In contrast to the extended Kalman filter, which is based on a linear
	approximation of the measurement equations, we use an iterative optimization
	technique which takes non-linearities into account. The approach
	has been successfully used in robot soccer, where it reliably maintained
	a joint pose estimate for the players and the ball.},
}