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 physically 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 ID 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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 25-42 |
| Number of pages | 18 |
| Journal | Robotics and Autonomous Systems |
| Volume | 49 |
| Issue number | 1-2 SPEC. ISS. |
| DOIs | |
| State | Published - Nov 30 2004 |
| Externally published | Yes |
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Keywords
- Qualitative knowledge representation
- Qualitative navigation
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computational Mechanics
Cite this
Egocentric qualitative spatial knowledge representation for physical robots. / Wagner, T.; Visser, Ubbo E; Herzog, O.
In: Robotics and Autonomous Systems, Vol. 49, No. 1-2 SPEC. ISS., 30.11.2004, p. 25-42.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Egocentric qualitative spatial knowledge representation for physical robots
AU - Wagner, T.
AU - Visser, Ubbo E
AU - Herzog, O.
PY - 2004/11/30
Y1 - 2004/11/30
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 physically 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 ID 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.
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 physically 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 ID 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.
KW - Qualitative knowledge representation
KW - Qualitative navigation
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UR - http://www.scopus.com/inward/citedby.url?scp=8344270864&partnerID=8YFLogxK
U2 - 10.1016/j.robot.2004.07.022
DO - 10.1016/j.robot.2004.07.022
M3 - Article
VL - 49
SP - 25
EP - 42
JO - Robotics and Autonomous Systems
JF - Robotics and Autonomous Systems
SN - 0921-8890
IS - 1-2 SPEC. ISS.
ER -