Egocentric qualitative spatial knowledge representation for physical robots

Thomas Wagner, Ubbo E Visser, Otthein Herzog

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Although recent (physical) robots have powerful sensors and actuators their abilities to show intelligent behavior is often limited. One key reason is the lack of an appropriate spatial representation. Spatial knowledge plays a crucial role in navigation, (self- and object-)localization, planning and reasoning for physical grounded robots. However, it is a major difficulty of most existing approaches that each of these tasks imposes heterogeneous requirements on the representation. In this paper, we propose an egocentric representation, which relies on 1-D ordering information that still provides sufficient allocentric information to solve navigation and (self- and object) localization tasks. Furthermore, we claim that our approach supports an efficient, incremental process based on a simple 1D-representation. We conclude with a more abstract qualitative spatial representation.

Original languageEnglish (US)
Title of host publicationAAAI Spring Symposium - Technical Report
Pages9-16
Number of pages8
Volume4
StatePublished - 2004
Externally publishedYes
Event2004 AAAI Spring Symposium - Stanford, CA, United States
Duration: Mar 22 2004Mar 24 2004

Other

Other2004 AAAI Spring Symposium
CountryUnited States
CityStanford, CA
Period3/22/043/24/04

Fingerprint

Knowledge representation
Navigation
Robots
Actuators
Planning
Sensors

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Wagner, T., Visser, U. E., & Herzog, O. (2004). Egocentric qualitative spatial knowledge representation for physical robots. In AAAI Spring Symposium - Technical Report (Vol. 4, pp. 9-16)

Egocentric qualitative spatial knowledge representation for physical robots. / Wagner, Thomas; Visser, Ubbo E; Herzog, Otthein.

AAAI Spring Symposium - Technical Report. Vol. 4 2004. p. 9-16.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wagner, T, Visser, UE & Herzog, O 2004, Egocentric qualitative spatial knowledge representation for physical robots. in AAAI Spring Symposium - Technical Report. vol. 4, pp. 9-16, 2004 AAAI Spring Symposium, Stanford, CA, United States, 3/22/04.
Wagner T, Visser UE, Herzog O. Egocentric qualitative spatial knowledge representation for physical robots. In AAAI Spring Symposium - Technical Report. Vol. 4. 2004. p. 9-16
Wagner, Thomas ; Visser, Ubbo E ; Herzog, Otthein. / Egocentric qualitative spatial knowledge representation for physical robots. AAAI Spring Symposium - Technical Report. Vol. 4 2004. pp. 9-16
@inproceedings{edb3ae4ce3574d2c9446871563d14c5f,
title = "Egocentric qualitative spatial knowledge representation for physical robots",
abstract = "Although recent (physical) robots have powerful sensors and actuators their abilities to show intelligent behavior is often limited. One key reason is the lack of an appropriate spatial representation. Spatial knowledge plays a crucial role in navigation, (self- and object-)localization, planning and reasoning for physical grounded robots. However, it is a major difficulty of most existing approaches that each of these tasks imposes heterogeneous requirements on the representation. In this paper, we propose an egocentric representation, which relies on 1-D ordering information that still provides sufficient allocentric information to solve navigation and (self- and object) localization tasks. Furthermore, we claim that our approach supports an efficient, incremental process based on a simple 1D-representation. We conclude with a more abstract qualitative spatial representation.",
author = "Thomas Wagner and Visser, {Ubbo E} and Otthein Herzog",
year = "2004",
language = "English (US)",
volume = "4",
pages = "9--16",
booktitle = "AAAI Spring Symposium - Technical Report",

}

TY - GEN

T1 - Egocentric qualitative spatial knowledge representation for physical robots

AU - Wagner, Thomas

AU - Visser, Ubbo E

AU - Herzog, Otthein

PY - 2004

Y1 - 2004

N2 - Although recent (physical) robots have powerful sensors and actuators their abilities to show intelligent behavior is often limited. One key reason is the lack of an appropriate spatial representation. Spatial knowledge plays a crucial role in navigation, (self- and object-)localization, planning and reasoning for physical grounded robots. However, it is a major difficulty of most existing approaches that each of these tasks imposes heterogeneous requirements on the representation. In this paper, we propose an egocentric representation, which relies on 1-D ordering information that still provides sufficient allocentric information to solve navigation and (self- and object) localization tasks. Furthermore, we claim that our approach supports an efficient, incremental process based on a simple 1D-representation. We conclude with a more abstract qualitative spatial representation.

AB - Although recent (physical) robots have powerful sensors and actuators their abilities to show intelligent behavior is often limited. One key reason is the lack of an appropriate spatial representation. Spatial knowledge plays a crucial role in navigation, (self- and object-)localization, planning and reasoning for physical grounded robots. However, it is a major difficulty of most existing approaches that each of these tasks imposes heterogeneous requirements on the representation. In this paper, we propose an egocentric representation, which relies on 1-D ordering information that still provides sufficient allocentric information to solve navigation and (self- and object) localization tasks. Furthermore, we claim that our approach supports an efficient, incremental process based on a simple 1D-representation. We conclude with a more abstract qualitative spatial representation.

UR - http://www.scopus.com/inward/record.url?scp=8344277569&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=8344277569&partnerID=8YFLogxK

M3 - Conference contribution

VL - 4

SP - 9

EP - 16

BT - AAAI Spring Symposium - Technical Report

ER -