Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Modeling a dynamic environment using a Bayesian multiple hypothesis approach
Artificial Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
RoboCup-98: Robot Soccer World Cup II
From Multiple Images to a Consistent View
RoboCup 2000: Robot Soccer World Cup IV
RoboCup 2001: Robot Soccer World Cup V
Plan-Based Control for Autonomous Soccer Robots (Preliminary Report)
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
Reliable Multi-robot Coordination Using Minimal Communication and Neural Prediction
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
Camera-based observation of football games for analyzing multi-agent activities
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
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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, 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 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.