Title
Developing The Bottom-up Attentional System of A Social Robot
Abstract
This paper describes the development of a 3- stage signalling framework to trigger a social robot's bottom- up reactive behavior inspired by a biological model. In the first stage, low-level firing of stimuli due to external sources is constructed through perception grounding. This is followed by a saliency classifier which fires-up high level salient signals that require attention and are used to trigger the robot's reactive behavior. The whole framework evolves primarily on the knowledge ontology that defines the characteristics of the social robot and the querying mechanism that correlates the perceived stimuli with the ontology to trigger the reactive behavior. We evaluated the performance of our system with timing metrics and we achieved good results for our application.
Year
DOI
Venue
2022
10.1109/ICRA46639.2022.9811759
IEEE International Conference on Robotics and Automation
DocType
Volume
Issue
Conference
2022
1
Citations 
PageRank 
References 
0
0.34
0
Authors
8
Name
Order
Citations
PageRank
Randy Gomez17628.11
Álvaro Páez200.34
Yu Fang300.34
Serge Thill402.37
L. Merino526419.87
Eric Nichols6474.22
Keisuke Nakamura718928.91
Heike Brock814.47