Rosemary Emery

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This paper describes an algorithm for generating compact 3D models of indoor environments with mobile robots. Our algorithm employs the expectation maximization algorithm to fit a lowcomplexity planar model to 3D data collected by range finders and a panoramic camera. The complexity of the model is determined during model fitting, by incrementally adding(More)
Decision making under uncertainty is a central problem in robotics and machine learning. This thesis explores three fundamental and intertwined aspects of the problem of learning to make decisions. The first is the problem of uncertainty. Classical optimal control techniques typically rely on perfect state information. Real world problems never enjoy such(More)
Creation of cooperative robot teams for complex tasks requires not only agents that can function well individually but also agents that can coordinate their actions. This paper presents several methods for collaboration and coordination in a team of soccerplaying robots. In our approach, fixed collaborative supporting behaviours allow for robots to aid each(More)
This paper describes an algorithm for generating compact 3D models of indoor environments with mobile robots. Our algorithm employs the expectation maximization algorithm to fit a lowcomplexity planar model to 3D data collected by range finders and a panoramic camera. The complexity of the model is determined during model fitting, by incrementally adding(More)
In this paper the hardware and software design of the CMU Hammerhead middle-size robot team are presented. The team consists of 4 fully autonomous robots with wireless communication and color vision. TeamBots, a Java-based software package, forms the robots' software architecture, while Clay, a TeamBots package for creating motor-schema based control(More)
Decision making under uncertainty is a central problem in robotics and machine learning. This thesis explores three fundamental and intertwined aspects of the problem of learning to make decisions. The first is the problem of uncertainty. Classical optimal control techniques typically rely on perfect state information. Real world problems never enjoy such(More)
The CMUMultiRobot Lab focuses on the study of team behavior in dynamic and uncertain environments. In order to further this research, we have developed an inexpensive autonomous robot platform, the Minnow. The CMU Hammerhead robot soccer team competes in the middle-size RoboCup competition using four of these Minnow robots. The 2001 CMU Hammerheads(More)
In this paper the hardware and software design of the CMU Hammerhead middle-size robot team are presented. The team consists of 4 fully autonomous robots with wireless communication and color vision. TeamBots, a Java-based software package, forms the robots' software architecture , while Clay, a TeamBots package for creating motor-schema based control(More)