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Paper WeP104.2

Blumenthal, Sebastian (GPS Gesellschaft fuer Produktionssysteme GmbH), Prassler, Erwin (Bonn-Rhein-Sieg Univ. of Applied Sciences), Fischer, Jan (Fraunhofer IPA), Nowak, Walter (GPS GmbH)

Towards Identification of Best Practice Algorithms in 3D Perception and Modeling

Scheduled for presentation during the Regular Sessions "Range Sensing III" (WeP104), Wednesday, May 11, 2011, 13:55−14:10, Room 3E

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on December 10, 2019

Keywords Range Sensing, Robotic Software, Middleware and Programming Environments

Abstract

Robots need a representation of their environment to reason about and to interact with it. Different 3D perception and modeling approaches exist to create such a representation, but they are not yet easily comparable. This work tries to identify best practice algorithms in the domain of 3D perception and modeling with a focus on environment reconstruction for robotic applications. The goal is to have a collection of refactored algorithms that are easily measurable and comparable.

The realization follows a methodology consisting of five steps. After a survey of relevant algorithms and libraries, common representations for the core data-types Cartesian point, Cartesian point cloud and triangle mesh are identified for use in harmonized interfaces. Atomic algorithms are encapsulated into four software components: the Octree component, the Iterative Closest Point component, the k-Nearest Neighbors search component and the Delaunay triangulation component. A sample experiment demonstrates how the component structure can be used to deduce best practice.

 

 

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