• Publications
  • Influence
Probabilistic robotics
Planning and navigation algorithms exploit statistics gleaned from uncertain, imperfect real-world environments to guide robots toward their goals and around obstacles.
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Markov Localization for Mobile Robots in Dynamic Environments
Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurateExpand
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Simultaneous Localization and Mapping with Sparse Extended Information Filters
In this paper we describe a scalable algorithm for the simultaneous mapping and localization (SLAM) problem. SLAM is the problem of acquiring a map of a static environment with a mobile robot. TheExpand
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Learning Metric-Topological Maps for Indoor Mobile Robot Navigation
  • S. Thrun
  • Computer Science, Mathematics
  • Artif. Intell.
  • 1 February 1998
Abstract Autonomous robots must be able to learn and maintain models of their environments. Research on mobile robot navigation has produced two major paradigms for mapping indoor environments:Expand
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Approximate solutions for partially observable stochastic games with common payoffs
Partially observable decentralized decision making in robot teams is fundamentally different from decision making in fully observable problems. Team members cannot simply apply single-agent solutionExpand
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Finding Approximate POMDP solutions Through Belief Compression
Recent research in the field of robotics has demonstrated the utility of probabilistic models for perception and state tracking on deployed robot systems. For example, Kalman filters and MarkovExpand
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Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results
This paper describes a scalable algorithm for the simultaneous mapping and localization (SLAM) problem. SLAM is the problem of determining the location of environmental features with a roving robot.Expand
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A guide to deep learning in healthcare
Here we present deep-learning techniques for healthcare, centering our discussion on deep learning in computer vision, natural language processing, reinforcement learning, and generalized methods. WeExpand
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Discovering Structure in Multiple Learning Tasks: The TC Algorithm
Recently, there has been an increased interest in “lifelong” machine learning methods, that transfer knowledge across multiple learning tasks. Such methods have repeatedly been found to outperformExpand
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Toward robotic cars
  • S. Thrun
  • Computer Science
  • CACM
  • 1 April 2010
This article advocates self-driving, robotic technology for cars. Recent challenges organized by DARPA have induced a significant advance in technology for autopilots for cars; similar to thoseExpand
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