M. Beetz

Publications533
h-index59
Citations16,718
Highly Influential Citations988
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Fast Point Feature Histograms (FPFH) for 3D registration
TLDR
This paper modifications their mathematical expressions and performs a rigorous analysis on their robustness and complexity for the problem of 3D registration for overlapping point cloud views, and proposes an algorithm for the online computation of FPFH features for realtime applications. Expand
Aligning point cloud views using persistent feature histograms
TLDR
This paper investigates the usage of persistent point feature histograms for the problem of aligning point cloud data views into a consistent global model, and estimates a set of robust 16D features which describe the geometry of each point locally. Expand
Towards 3D Point cloud based object maps for household environments
TLDR
The novel techniques include statistical analysis, persistent histogram features estimation that allows for a consistent registration, resampling with additional robust fitting techniques, and segmentation of the environment into meaningful regions. Expand
KNOWROB — knowledge processing for autonomous personal robots
  • M. Tenorth, M. Beetz
  • Computer Science
  • IEEE/RSJ International Conference on Intelligent…
  • 10 October 2009
TLDR
KINDROB is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference — knowledge processing features that are particularly necessary for autonomous robot control. Expand
The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition
TLDR
This paper presents first results of an automatic method for segmenting the observed motions into semantic classes, and describes how the data can be integrated in a knowledge-based framework for reasoning about the observations. Expand
Persistent Point Feature Histograms for 3D Point Clouds
TLDR
This paper proposes a novel way of characterizing the local geometry of 3D points, using persistent feature histograms, and shows that geometric primitives have unique signatures in this feature space, preserved even in the presence of additive noise. Expand
Real-time compression of point cloud streams
TLDR
This work presents a novel lossy compression approach for point cloud streams which exploits spatial and temporal redundancy within the point data and presents a technique for comparing the octree data structures of consecutive point clouds. Expand
Learning informative point classes for the acquisition of object model maps
TLDR
A set of methods for building informative and robust feature point representations, used for accurately labeling points in a 3D point cloud, based on the type of surface the point is lying on, are proposed. Expand
KnowRob: A knowledge processing infrastructure for cognition-enabled robots
TLDR
This article introduces the KnowRob knowledge processing system, a system specifically designed to provide autonomous robots with the knowledge needed for performing everyday manipulation tasks, and evaluates the system’s scalability and present different integrated experiments that show its versatility and comprehensiveness. Expand
Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot Minerva
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… Expand
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