Proactive Model for Handling Conflicts in Sensor Data Fusion Applied to Robotic Systems
English
Neyens, Gilles[University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Zampunieris, Denis[University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2019
Proceedings of the 14th International Conference on Software Technologies (ICSOFT), 2019 Prague, Czech Republic, 26 - 28 July, 2019
SCITEPRESS
468-474
Yes
No
International
978-989-758-379-7
14th International Conference on Software Technologies (ICSOFT), 2019 Prague, Czech Republic, 26 - 28 July, 2019
26 - 28 July, 2019
INSTICC
Prague
Czech Republic
[en] Decision Support System ; System Software ; Proactive Systems ; Robotics ; Proactive computing
[en] Robots have to be able to function in a multitude of different situations and environments. To help them achieve this, they are usually equipped with a large set of sensors whose data will be used in order to make decisions. However, the sensors can malfunction, be influenced by noise or simply be imprecise. Existing sensor fusion techniques can be used in order to overcome some of these problems, but we believe that data can be improved further by computing context information and using a proactive rule-based system to detect potentially conflicting data coming from different sensors. In this paper we will present the architecture and scenarios for a generic model taking context into account.