Skip to search formSkip to main contentSkip to account menu

Fast Point Feature Histograms (FPFH) for 3D registration

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.
View on IEEE (opens in a new tab)

Aligning point cloud views using persistent feature histograms

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.
View on IEEE (opens in a new tab)

Towards 3D Point cloud based object maps for household environments

View via Publisher (opens in a new tab)

KNOWROB — knowledge processing for autonomous personal robots

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.
View on IEEE (opens in a new tab)

The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition

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.
View on IEEE (opens in a new tab)

Real-time compression of point cloud streams

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.
View on IEEE (opens in a new tab)

Persistent Point Feature Histograms for 3D Point Clouds

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

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.
View on SAGE (opens in a new tab)

Learning informative point classes for the acquisition of object model maps

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.
View on IEEE (opens in a new tab)

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…
View on SAGE (opens in a new tab)
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)