Technical University of Munich

@article{schmitt_cooperative_2002,
 author = {T Schmitt and R Hanek and M Beetz and S Buck and B Radig},
 title = {Cooperative Probabilistic State Estimation for Vision-based Autonomous
	Mobile Robots},
 journal = {{IEEE} Transactions on Robotics and Automation},
 year = {2002},
 volume = {18},
 number = {5},
 month = {oct},
 abstract = {With the services that autonomous robots are to provide becoming more
	demanding, the states that the robots have to estimate become more
	complex. In this article, we develop and analyze a probabilistic,
	vision-based state estimation method for individual, autonomous robots.
	This method enables a team of mobile robots to estimate their joint
	positions in a known environment and track the positions of autonomously
	moving objects. The tate estimators of different robots cooperate
	to increase the accuracy and reliability of the estimation process.
	This cooperation between the robots enables them to track temporarily
	occluded objects and to faster recover their position after they
	have lost track of it. The method is empirically validated based
	on experiments with a team of physical robots.},
}