Fast Point Feature Histograms (FPFH) for 3D registration
- R. Rusu, Nico Blodow, M. Beetz
- Computer ScienceIEEE International Conference on Robotics and…
- 12 May 2009
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.
Aligning point cloud views using persistent feature histograms
- R. Rusu, Nico Blodow, Zoltán-Csaba Márton, M. Beetz
- Computer ScienceIEEE/RSJ International Conference on Intelligent…
- 14 October 2008
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.
Towards 3D Point cloud based object maps for household environments
- R. Rusu, Zoltán-Csaba Márton, Nico Blodow, Mihai Emanuel Dolha, M. Beetz
- Environmental ScienceRobotics Auton. Syst.
- 1 November 2008
KNOWROB — knowledge processing for autonomous personal robots
- Moritz Tenorth, M. Beetz
- Computer ScienceIEEE/RSJ International Conference on Intelligent…
- 10 October 2009
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.
The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition
- Moritz Tenorth, Jan Bandouch, M. Beetz
- Computer ScienceIEEE 12th International Conference on Computer…
- 1 September 2009
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.
Real-time compression of point cloud streams
- J. Kammerl, Nico Blodow, R. Rusu, Suat Gedikli, M. Beetz, E. Steinbach
- Computer Science, Environmental ScienceIEEE International Conference on Robotics and…
- 14 May 2012
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.
Persistent Point Feature Histograms for 3D Point Clouds
- R. Rusu, Zoltán-Csaba Márton, Nico Blodow, M. Beetz
- Computer Science
- 2008
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.
KnowRob: A knowledge processing infrastructure for cognition-enabled robots
- Moritz Tenorth, M. Beetz
- Computer ScienceInt. J. Robotics Res.
- 1 April 2013
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.
Learning informative point classes for the acquisition of object model maps
- R. Rusu, Zoltán-Csaba Márton, Nico Blodow, M. Beetz
- Computer ScienceInternational Conference on Control, Automation…
- 1 December 2008
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.
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…
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