Reference : Context-based Selection and Execution of Robot Perception Graphs |
Scientific congresses, symposiums and conference proceedings : Paper published in a book | |||
Engineering, computing & technology : Computer science | |||
http://hdl.handle.net/10993/22384 | |||
Context-based Selection and Execution of Robot Perception Graphs | |
English | |
Hochgeschwender, Nico ![]() | |
Olivares Mendez, Miguel Angel [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
Voos, Holger ![]() | |
Kraetzschmar, Gerhard K. [> >] | |
Sep-2015 | |
20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'15) | |
Yes | |
No | |
International | |
20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'15) | |
from 8-09-2015 to 11-09-2015 | |
[en] knowledge representation ; computer vision ; illumination invariant | |
[en] To perform a wide range of tasks service robots
need to robustly extract knowledge about the world from the data perceived through the robot’s sensors even in the presence of varying context-conditions. This makes the design and devel- opment of robot perception architectures a challenging exercise. In this paper we propose a robot perception architecture which enables to select and execute at runtime different perception graphs based on monitored context changes. To achieve this the architecture is structured as a feedback loop and contains a repository of different perception graph configurations suitable for various context conditions. | |
Researchers ; Professionals ; Students | |
http://hdl.handle.net/10993/22384 |
File(s) associated to this reference | ||||||||||||||
Fulltext file(s):
| ||||||||||||||
All documents in ORBilu are protected by a user license.