Open AccessBook
Probabilistic Robotics
TLDR
This research presents a novel approach to planning and navigation algorithms that exploit statistics gleaned from uncertain, imperfect real-world environments to guide robots toward their goals and around obstacles.Abstract:
Planning and navigation algorithms exploit statistics gleaned from uncertain, imperfect real-world environments to guide robots toward their goals and around obstacles.read more
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Book
Machine Learning : A Probabilistic Perspective
TL;DR: This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach, and is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
MonographDOI
Planning Algorithms: Introductory Material
TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Book
Computer Vision: Algorithms and Applications
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI
Locating the nodes: cooperative localization in wireless sensor networks
Neal Patwari,Joshua N. Ash,Spyros Kyperountas,Alfred O. Hero,Randolph L. Moses,Neiyer S. Correal,Neiyer S. Correal +6 more
TL;DR: Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements in wireless sensor networks.
Journal ArticleDOI
Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters
TL;DR: In this article, the authors proposed an approach to compute an accurate proposal distribution, taking into account not only the movement of the robot, but also the most recent observation, which drastically decreases the uncertainty about the robot's pose in the prediction step of the filter.
References
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BookDOI
Sequential Monte Carlo methods in practice
TL;DR: This book presents the first comprehensive treatment of Monte Carlo techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modeling, neural networks, optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection.
Book
The EM algorithm and extensions
TL;DR: The EM Algorithm and Extensions describes the formulation of the EM algorithm, details its methodology, discusses its implementation, and illustrates applications in many statistical contexts, opening the door to the tremendous potential of this remarkably versatile statistical tool.
Proceedings Article
Coordination for Multi-Robot Exploration and Mapping
Reid Simmons,David Apfelbaum,Wolfram Burgard,Dieter Fox,Mark Moors,Sebastian Thrun,Håkan L. S. Younes +6 more
TL;DR: This paper addresses the problem of exploration and mapping of an unknown environment by multiple robots by developing an on-line approach to likelihood maximization that uses hill climbing to find maps that are maximally consistent with sensor data and odometry.
Journal ArticleDOI
Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva
Sebastian Thrun,Michael Beetz,Maren Bennewitz,Wolfram Burgard,Armin B. Cremers,Frank Dellaert,Dieter Fox,Dirk Hähnel,Charles R. Rosenberg,Nicholas Roy,Jamieson Schulte,Dirk Schulz +11 more
Abstract: This paper describes Minerva, an interactive tour-guide robot that was successfully deployed in a Smithsonian museum. Minerva’s software is pervasively probabilistic, relying on explicit representations of uncertainty in perception and control. This article describes Minerva’s major software components, and provides a comparative analysis of the results obtained in the Smithsonian museum. During two weeks of highly successful operation, the robot interacted with thousands of people, both in the museum and through the Web, traversing more than 44km at speeds of up to 163 cm/sec in the unmodie d museum.