by T Schmitt, R Hanek, S Buck and M Beetz
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 paper, we develop and analyze a probabilistic, vision-based state estimation method for individual, autono-mous 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 state 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.
Reference:
Cooperative Probabilistic State Estimation fo Vision-based Autonomous Soccer Robots (T Schmitt, R Hanek, S Buck and M Beetz), In RoboCup International Symposium 2001, 2001.
Bibtex Entry:
@inproceedings{schmitt_cooperative_2001-2,
author = {T Schmitt and R Hanek and S Buck and M Beetz},
title = {Cooperative Probabilistic State Estimation fo Vision-based Autonomous
Soccer Robots},
booktitle = {{RoboCup} International Symposium 2001},
year = {2001},
address = {Seattle, {USA}},
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 paper, we develop and analyze a probabilistic, vision-based
state estimation method for individual, autono-mous 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 state 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.},
}