• Publications
  • Influence
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
  • 2,987
  • 426
A large-scale hierarchical multi-view RGB-D object dataset
Over the last decade, the availability of public image repositories and recognition benchmarks has enabled rapid progress in visual object category and instance detection. Today we are witnessing theExpand
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The dynamic window approach to collision avoidance
This approach, designed for mobile robots equipped with synchro-drives, is derived directly from the motion dynamics of the robot. In experiments, the dynamic window approach safely controlled theExpand
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Robust Monte Carlo localization for mobile robots
Mobile robot localization is the problem of determining a robot’s pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo LocalizationExpand
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PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
Estimating the 6D pose of known objects is important for robots to interact with the real world. The problem is challenging due to the variety of objects as well as the complexity of a scene causedExpand
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Monte Carlo localization for mobile robots
To navigate reliably in indoor environments, a mobile robot must know where it is. Thus, reliable position estimation is a key problem in mobile robotics. We believe that probabilistic approaches areExpand
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DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time
We present the first dense SLAM system capable of reconstructing non-rigidly deforming scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our DynamicFusion approachExpand
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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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Adapting the Sample Size in Particle Filters Through KLD-Sampling
  • D. Fox
  • Computer Science, Mathematics
  • Int. J. Robotics Res.
  • 1 December 2003
Over the past few years, particle filters have been applied with great success to a variety of state estimation problems. In this paper we present a statistical approach to increasing the efficiencyExpand
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RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments
RGB-D cameras are novel sensing systems that capture RGB images along with per-pixel depth information. In this paper we investigate how such cameras can be used in the context of robotics,Expand
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