Semi-automatic acquisition of symbolically-annotated 3D-models of office environments

Michael Beetz; Markus Giesenschlag; Roman Englert; Eberhard Guelch; Armin B. Cremers

Semi-automatic acquisition of symbolically-annotated 3D-models of office environments

Michael Beetz, Markus Giesenschlag, Roman Englert, Eberhard Guelch, Armin B. Cremers

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

This paper describes a semi-automatic method for acquiring SA3D maps, maps that contain hierarchically structured 3D models of static, task relevant objects in the environment. Map acquisition is implemented as a two step process. In the first step, the robot acquires an approximate model that represents regions that might contain objects and indicate possible occluding objects. This approximate model is then used to compute appropriate locations from where camera images should be taken. Object models are reconstructed interactively through human operators who place wireframe models in the camera images captured by the robot. The method is implemented and validated on an autonomous mobile robot.

Original language	English
Pages (from-to)	2280-2285
Number of pages	6
Journal	Proceedings - IEEE International Conference on Robotics and Automation
Volume	3
State	Published - 1 Jan 1999
Externally published	Yes
Event	Proceedings of the 1999 IEEE International Conference on Robotics and Automation, ICRA99 - Detroit, MI, USA Duration: 10 May 1999 → 15 May 1999

ASJC Scopus subject areas

Software
Control and Systems Engineering
Artificial Intelligence
Electrical and Electronic Engineering

Cite this

@article{57fedb7589c24b149d9c92f299297d8e,

title = "Semi-automatic acquisition of symbolically-annotated 3D-models of office environments",

abstract = "This paper describes a semi-automatic method for acquiring SA3D maps, maps that contain hierarchically structured 3D models of static, task relevant objects in the environment. Map acquisition is implemented as a two step process. In the first step, the robot acquires an approximate model that represents regions that might contain objects and indicate possible occluding objects. This approximate model is then used to compute appropriate locations from where camera images should be taken. Object models are reconstructed interactively through human operators who place wireframe models in the camera images captured by the robot. The method is implemented and validated on an autonomous mobile robot.",

author = "Michael Beetz and Markus Giesenschlag and Roman Englert and Eberhard Guelch and Cremers, {Armin B.}",

year = "1999",

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day = "1",

language = "English",

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journal = "Proceedings - IEEE International Conference on Robotics and Automation",

issn = "1050-4729",

publisher = "Institute of Electrical and Electronics Engineers",

note = "Proceedings of the 1999 IEEE International Conference on Robotics and Automation, ICRA99 ; Conference date: 10-05-1999 Through 15-05-1999",

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TY - JOUR

T1 - Semi-automatic acquisition of symbolically-annotated 3D-models of office environments

AU - Beetz, Michael

AU - Giesenschlag, Markus

AU - Englert, Roman

AU - Guelch, Eberhard

AU - Cremers, Armin B.

PY - 1999/1/1

Y1 - 1999/1/1

N2 - This paper describes a semi-automatic method for acquiring SA3D maps, maps that contain hierarchically structured 3D models of static, task relevant objects in the environment. Map acquisition is implemented as a two step process. In the first step, the robot acquires an approximate model that represents regions that might contain objects and indicate possible occluding objects. This approximate model is then used to compute appropriate locations from where camera images should be taken. Object models are reconstructed interactively through human operators who place wireframe models in the camera images captured by the robot. The method is implemented and validated on an autonomous mobile robot.

AB - This paper describes a semi-automatic method for acquiring SA3D maps, maps that contain hierarchically structured 3D models of static, task relevant objects in the environment. Map acquisition is implemented as a two step process. In the first step, the robot acquires an approximate model that represents regions that might contain objects and indicate possible occluding objects. This approximate model is then used to compute appropriate locations from where camera images should be taken. Object models are reconstructed interactively through human operators who place wireframe models in the camera images captured by the robot. The method is implemented and validated on an autonomous mobile robot.

UR - http://www.scopus.com/inward/record.url?scp=0032661125&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0032661125

SN - 1050-4729

VL - 3

SP - 2280

EP - 2285

JO - Proceedings - IEEE International Conference on Robotics and Automation

JF - Proceedings - IEEE International Conference on Robotics and Automation

T2 - Proceedings of the 1999 IEEE International Conference on Robotics and Automation, ICRA99

Y2 - 10 May 1999 through 15 May 1999

ER -

Semi-automatic acquisition of symbolically-annotated 3D-models of office environments

Abstract

ASJC Scopus subject areas

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